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In an era where technology is essentially reprogramming the DNA of almost all industries, artificial intelligence emerges as a revolutionary titan. Particularly in the adrenaline-charged theater of forex trading, AI is not just a supporting act; it has become a headliner catalyzing transformations as exhilarating as they are intricate. With every tick of the clock, AI codes hold the power to go through a maze of data, that do not just amplify gains but also radically shift the landscape for experts and newbies alike. making decisions However, the rise of AI is not a one-sided narrative of triumph. It incorporates a double-edged sword, opening doors to a world of prospects while simultaneously tossing in new complexities that traders cannot afford to ignore. This article digs deep into the multifaceted impact of AI on the ever-fluctuating universe of online trading, revealing how it is shaking things up and what traders should be aware of in this swiftly evolving domain. How Artificial Intelligence can impact the future of online trading “Artificial intelligence will . Follow that out further, by about 2045, we will have multiplied the intelligence - the human biological machine intelligence of our civilization - a billion-fold.” – Ray Kurzweil, American inventor, and futurist. reach human levels by around 2029 In the sprawling digital expanse, a newcomer is painting the canvas of online trading, i.e., Artificial Intelligence. It is the artisan blending the brushstrokes of human cognition, endowing software with the ability to self-learn and accomplish delicate tasks. Particularly in the realm of online trading, AI is increasingly viewed as an indispensable asset for sifting through market data, discerning patterns, and forecasting looming market shifts. While AI is still a budding affair, its enchantment in trading is unmistakable. The numbers, as presented by Fortune Business Insights, are a testament. The algorithmic trading market's valuation was already at a staggering USD 2.03 billion in 2022, and it is slated to burgeon to a jaw-dropping USD 3.56 billion by 2030. This heralds a Compound Annual Growth Rate (CAGR) of 7.2%. The takeaway? An escalating reliance on AI-led algorithmic strategies by traders. What AI brings to the trading table is a dexterity beyond human means. The remarkable agility of AI in real-time market assessment enables it to deliver rapid and meticulous insights. Analyzing copious amounts of market data in real time, AI mechanisms swiftly pinpoint market dynamics, determine trends, and unveil golden trading opportunities. This immediate data processing empowers traders, allowing decisions that outpace conventional manual analysis. Another prominent role of AI in forex trading is its capability to facilitate novice traders. For the greenhorn traders, the forex market often appears as a complex maze. AI is like a mentor that substantially bridges the historically challenging learning chasm in forex, granting newcomers real-time market analytics, predictive tools, and more. With AI as the guide, the uncharted terrain of trading becomes less intimidating, opening avenues that were once exclusive to the trading elite. Overall, Artificial Intelligence is not just another buzzword; it is the harbinger of a new era in digital trading. As the wheels of innovation churn, the melding of AI and online trading promises a horizon filled with untapped opportunities, setting the tone for a ground-breaking epoch in trading. Here is an in-depth overview exploring the various ways artificial intelligence is shaping the industry, with a focus on its long-term impact in the years ahead. Enhanced trading analysis and data processing – Improved predictive power The vastness of the financial world presents data in unimaginable quantities, from decades of historical price data to the daily dose of news articles. AI thrives in this space, effortlessly going through mountains of information. Where a human might struggle to keep up, AI consistently and efficiently processes data, identifying repeatable patterns and trends that often remain obscured to us. The result? Traders are equipped with sharper insights and clearer pictures of market landscapes. Additionally, predicting market movements has always been the Holy Grail of . With AI, this task comes closer to reality. By diving deep into historical and current data, AI showcases an uncanny ability to forecast future currency shifts. Gone are the days of pure speculation; today's traders, armed with AI-driven predictions, can make decisions rooted in robust data analysis, greatly reducing the unpredictable risks once synonymous with forex trading. trading Also, it is more than mere digits and numbers on a graph; today's trading scene is heavily influenced by the sheer power of headlines and the social media realm. AI, with its natural language processing capabilities, can gauge the digital world's emotional ebb and flow, crafting those raw sentiments into actionable trade decisions. In a universe where a single tweet or post can tip financial scales, AI can ensure traders always have the upper hand. Eventually, from streamlining complex analyses to providing notable predictive power, AI is birthing a system that is swifter, more intuitive, and data-reliant than we have ever glimpsed. Automated trading systems and AI robots AI algorithms present the online trading world with another revolutionary tool: Automated trading systems. Pulsating with AI codes, these automated systems unearth trading opportunities, liberating traders from the tediousness of manual ventures. Not only do they execute trades with impeccable timing based on set criteria, but they also bring the potential for consistent performance by back-testing and fine-tuning trading strategies. Envision a trading confidant, attuned to your ambitions, your thresholds, and your risk boundaries. These new-age AI bots do just that. They resonate with the traders and are customizable allies, able to reflect a trader's aspirations. In other words, they are dynamic — adjusting their strategies to the market situation, ensuring they are always poised for maximum profitability. Another essential consideration is that automated trading systems, much like the financial markets, never rest. Their unwavering vigilance stands as a hallmark feature. Whether it is midnight or noon, these systems are always alert, ready to react instantly to any market shift. The beauty of it? No human intervention is required most of the time. While traders rest, the AI-imbued system continues to safeguard and grow their investments. High-Frequency Trading High-frequency trading refers to the rapid execution of a large number of trades within split seconds and AI is taking it to the next level. For traders, the fusion of AI with high-frequency trading can be a game-changer. Whether it is the ability to capitalize on tiny price differences that were previously impossible to catch, or the chance to dive into the market during times of amplified volatility, the opportunities can be vast with high-frequency algo trading. AI-powered risk management Traditional risk management often feels like navigating through a fog—there is only so much a human can see. Here AI functions as the light that cuts through the fog by analyzing complex market data. From identifying precarious market conditions to sniffing out market manipulation, AI algorithms provide a comprehensive risk assessment. New traders, especially, find this an invaluable shield against the hidden pitfalls of forex trading. Moreover, being humans, emotions can sometimes get the better of us—often at the least opportune moments, like during trading. AI serves as an emotional firewall, making data-based decisions devoid of human biases and glitches. The outcome? Significantly enhanced risk management, where every move is calculated and rational, not reactive. By combining unparalleled data analytics with an immunity to emotional sway, AI is definitely fortifying the future of risk management in online trading. Some emerging challenges related to AI and forex trading While AI offers a promising horizon in online trading, it is also essential to recognize and navigate the accompanying challenges with foresight. Some of them are: Just as the human mind thrives on quality education, AI codes flourish on high-quality data. An AI's prediction is as good as the data it consumes. It is imperative to have diligent data management processes, ensuring data's accuracy, reliability, and timeliness. Furthermore, in an age of increasing cyber threats, the security of financial data is paramount. One breach and trust can crumble. Data Quality and Security: The magnetism of AI can sometimes overshadow human intuition. Overdependence on AI tools might marginalize human judgment, which remains crucial. An unforeseen situation, or a mere technical fault in the AI system, can amplify risks if traders sideline their instinct. Over-reliance on Technology: As the fusion of AI and finance thickens, so do concerns about its . Questions of job displacement, privacy infringements, and adherence to ethical norms surface. As we thread this new era, a balanced approach—emphasizing transparency, accountability, and oversight—is crucial to harness AI's potential without discarding ethical considerations. Ethical and Regulatory Concerns: societal impacts Speed is of the essence in trading and with AI-driven high-frequency trading, it is supersonic. While this rapidity can be an asset, it is also a potential destabilizer. AI algorithms can set off colossal buy or sell tides in a moment, leading to unpredictable market movements like flash crashes or sudden price surges. Market Volatility: Bottom line Artificial Intelligence is undeniably making waves in the world of online trading, unlocking opportunities that were previously unimaginable. Its adeptness at churning through heaps of data and pinpointing hidden trends presents an enhanced dimension of market analysis. Yet, amidst this AI-driven metamorphosis, the seasoned wisdom, gut feeling, and strategic foresight of human traders cannot be pushed aside. For the ultimate proficiency in online trading, it is not about choosing one over the other, but rather cultivating a harmonious blend of AI precision with human insight. The true promise of the future lies in this balanced fusion.

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The world of data has changed dramatically over the past decade. Traditional databases, which were designed to store information in a structured format, have evolved into massive warehouses of unstructured data that sit on multiple servers across different locations. Not too long ago, we were used to seeing monolithic systems dominated by behemoths, the likes of Oracle and IBM. If you are an analyst or business user who needs access to this type of data—and who doesn't?—it meant slow-moving systems that were incredibly difficult to manage. The birth of a new software stack The increasing complexity of systems eventually drove the need for modern software stacks that could help organizations run complex applications while managing to stay cost-effective. The open source movement helped with this, by dramatically decreasing the cost of putting complex applications together such as Elastic Search for full-text search and PyTorch for modeling. Robust packaging and operations of the software improved usability, stability, and economics of the system. The (MDS), which has seen a lot of traction over the past decade, builds on the open source movement and is a collection of ideas, tools and methodologies intended to build the enterprise data stack.​ Modern Data Stack Challenges in scaling MDS In the 2010s, we saw rapid adoption of open source tools within the MDS. However, post their initial success a lot of organizations’ initiatives around these ran into challenges when it came to scaling them: The due to the number of tools, configurations, methodologies, and interactions that organizations and teams had to keep up with was overwhelming, leading to burnout and high attrition rates among talent cognitive overload The associated with these technologies was incredibly steep. One has to understand that most of these open source tools were built at sophisticated organizations such as Netflix, Google, and Uber and don’t necessarily suit the needs of organizations that have smaller deployments–a fraction of the scale. learning curve The pace of innovation in the space also meant . With the pace at which newer, better, faster, more efficient tools were arriving on the scene engineers had to learn and unlearn rapidly. shorter lifespans for newer technologies The data science community is one that has several conflicting viewpoints, resulting in a (what’s best for their business). More often than not, the only way to overcome this challenge is by building, which is not only expensive but time-consuming. lack of clarity around what approach one needs to adopt If you’ve been following hype cycles such as Gartner, it’s probably no surprise for you to learn that (which arrives much faster than it did probably a decade ago). Technologies like Hadoop, NoSQL, and Deep Learning which were considered “hot” not too long ago have already passed their peak of the Gartner hype cycle. technology investments have an end-date Points #1 and #2 have played a major role in adding to the stress levels in the industry, and also limiting the talent available for adopting and using technologies. We’ve seen a similar trend in the DevOps space, with the supply of developer talent not meeting the demand for new digital services. about this problem - which has been leading to high burnout, and the average career span of a professional developer being less than 20 years. He recently posted a thread where he did a deep-dive into the complexity in the developer-led landscape, and we can’t help but notice several parallels between what he claims and the MLOps space.​ Tyler Jewell of Dell Capital has been quite vocal Points #3 and #4 highlight the plight of today's data folks–if solving problems wasn’t enough, they end up spending more time trying to figure out “how” they can proceed and solve problems without being able to give much thought to what needs to be done, or the expected outcome. A change is coming… We’re seeing a shift in the data tools used by organizations, driven by an increased recognition that many of them have no choice but to rely on third-party vendors for their infrastructure needs. This is not only due to budget constraints but other constraints as well, such as data security and provenance. In addition, there’s an increased demand for automated processes that allow enterprises to easily migrate workloads from one provider to another without disrupting operations or causing downtime. We’re seeing the effects of these within industries like financial services where data management is often critical for success (for example, credit rating agencies). As a result of all these as well as the challenges listed above, there have been several developments in the community: ​ Organizations are increasingly emphasizing the need to build , giving rise to tools that focus on data quality and data governance. trust in their data There is growing emphasis on Machine Learning and Data Science initiatives being tied to outcomes, and business models that are explicitly . aligned to specific business use cases Ever increasing cost and complexity are resulting in consolidation through feature extensions, acquisitions and integrations. Snowflake, for example, is rapidly growing its list of partners to become a full analytical application stack. Considering the complexity post model deployment, we’re seeing an emergence of tools such as , which help estimate model performance, detect drift, and improve models in production through iterative deployments. We’re seeing this as a way for businesses to close the loop between the business, data, and the model. NannyML A new organization, , emerged to bring together the essential building blocks for Artificial Intelligence applications. They’ve been working on building a , which aims to drown the noise created due to the introduction of a plethora of tools that claim to be the “latest and greatest”, and help non-tech companies level up fast. AI Infrastructure Alliance Canonical Stack for Machine Learning The definition of the MDS is being extended to include data products, apps, and other elements. This is making MDS full-stack. and services are emerging that slice the space based on target users (e.g. data scientists vs. analysts), skill availability, and time to outcome realization. New products The MDS user base is expanding to include the analytics teams and business users. This is resulting in improved user experience, low-code interfaces, and automation. And finally, we’re seeing an emergence of approaches such as the “ ”, which is essentially a deconstruction of the MDS and the MLOps stacks. These approaches emphasize relevance for the business as well as the downstream consumption of generated features to produce business value. Post-Modern Stack ​ What this means Consolidation of tools and platforms, simpler platform developments, and the use of managed services is happening across the industry. This is stemming from the need for businesses to cope with complexity. It’s an exciting time to be a part of this space, and I can’t wait to see how the landscape evolves over the course of the year. At Scribble Data, (the company that I have co-founded) we are keenly aware of this evolution as it is happening. We focus on one specific problem - feature engineering for advanced analytics and data science use cases. This problem space has steadily grown in terms of importance and has evolved in ways that are consistent with the above points. With the right technology mix and solution focus, it is possible to align product value to use cases, while achieving 5x faster time to value (TTV) for each use case. Also Published Here

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Solving the stablecoin dilemma is paramount to crypto’s survival and success as our industry matures. Without a secure, capitally efficient, and decentralized stablecoin, it will be extremely difficult to onboard institutional and retail capital. What are stablecoins? Stablecoins are cryptocurrencies designed to maintain a peg with another currency, asset, or financial instrument. They are most commonly used as decentralized analogs to FIAT currencies, such as USD, EUR, and GBP. This provides traders a more “stable” alternative to historically volatile assets like ETH and BTC. What is the history of stablecoins? were introduced in 2014 by BitUSD (BITUSD) and NuBits (USNBT) and they were collateralized using different baskets of cryptocurrencies. While both of these tokens were revolutionary during their time, neither have managed to succeed at the one key task they were created to carry out, to maintain a “stable” peg with the US dollar. Both stablecoins have since lost their pegs and all but faded into oblivion, but their hurdles and trajectories would foreshadow one of crypto’s biggest unsolved problems, . The first stablecoins “The Stablecoin Trilemma” The Stablecoin Trilemma dictates that no one stablecoin can satisfy all 3 conditions: Price/Peg Stability - ie. The ability to constantly be traded at 1 USD. Capital Efficiency - ie. Having to lock up ≤ 1 USD to mint 1 USD stablecoin. Decentralization - Not relying on centralized custodians to manage collateral. What are the different types of stablecoin implementations? This stablecoin implementation problem has been tackled by crypto’s best and brightest to widely varying degrees of success, however, a perfect solution has yet to be found. As such, there are multiple different implementation strategies, each with its own unique tradeoffs. Broadly, these strategies can be split into two main categories, collateralized stablecoins and algorithmic (aka. uncollateralized) stablecoins. Collateralized Stablecoins A collateralized stablecoin is any cryptocurrency that is either partially or completely backed by collateral held in a treasury or reserve. This backing helps to ensure that the value of a collateralized stablecoin does not fall below its peg. Using USDC as an example, if 1 USDC was traded below 1 USD in value, traders would arbitrage the difference by purchasing USDC and redeeming it for 1 USD each. The inherent issue with FIAT collateralized stablecoins is the centralized nature of the collateral reserves. This opens up token holders to institutional risks like bankruptcy or mismanagement of funds. Collateralized backings are not limited to FIAT currencies alone. As it stands, there are stablecoins such as DAI and sUSD which are collateralized with other cryptocurrencies (namely, ETH and SNX respectively). These stablecoins can mitigate the centralized risk factors associated with FIAT-backed stables, however, due to the inherent volatility of most crypto assets, they require over-collateralized positions (ie 4:1 for USD) in order to maintain their pegs. This system is significantly safer but also much more capitally inefficient for end users. Algorithmic Stablecoins Algorithmic stablecoins are assets that do not rely on collateral reserves to maintain their peg. Instead, they utilize smart contracts to buy, sell, or burn tokens to respond to market supply and demand. In essence, algorithmic stablecoins maintain their pegs by mechanistically controlling their circulating supplies. Examples of algorithmic stablecoins include $FRAX and $UXD. Algorithmic stablecoins are inherently decentralized and fairly capitally efficient, however, their pegging mechanisms have greater sensitivity to extreme market conditions and attacks. $FRAX operates under a fractionally collateralized system, where each $FRAX is partially collateralized by fiat-backed stablecoins and partially backed by its own token, $FXS. The Frax collateralization ratio determines the ratio between collateral (ie. USDC) and algorithm ($FXS) that makes up the $1 FRAX value. An important requirement for $FRAX to function smoothly is to have deep liquidity with other stablecoins (ie. USDC and USDT). The FRAX+3Crv Pool on Curve Finance has nearly 1.1b USD of liquidity to help ensure as little slippage as possible when making trades. $UXD is a “delta-neutral” stablecoin that works by taking deposits, such as $ETH, and using those deposits as collateral to short an equivalent amount of perpetual swap contracts or dated futures. This balanced pair of the $ETH long and 1x ETH-USD short creates a delta neutral position with a value of $1 for each $UXD. If the price of $UXD < $1, arbitrageurs can redeem their $UXD for $1 of collateral assets (currently limited to ETH, BTC, and SOL) to make a profit. Conversely, if the price of $UXD > $1, arbitrageurs can mint $UXD at a cost of $1 per $UXD to make a profit. This mechanism allows UXD to consistently maintain its peg. Currently, $UXD and $FRAX seem to be the front-runners for solutions to the as they are fully decentralized and capital-efficient. What remains is for them to continue to prove their stability over time. stablecoin dilemma Why are stablecoins important/necessary? The vision is simple: Decentralized finance requires decentralized currencies. As crypto is still an emerging market, volatility is to be expected and perhaps even welcomed. However, there must exist an on-chain alternative to “stable” FIAT currencies to act as trading pairs on DEXs and as a means to store capital long-term. About Dan Edlebeck Dan is a co-founder of Sei Network. Active in the Cosmos ecosystem, Dan led Sentinel for the past 2 years. Over the past five years, Dan has held several roles within crypto organizations including leading marketing for Blockparty and operating a PR agency, deedle connects. He is a strong advocate for the power of an inclusive financial system built on web3 infrastructure. About Sei Network is the first orderbook-specific L1 blockchain. It is built using the Cosmos SDK and Tendermint core and features a built-in central limit orderbook (CLOB) module. Decentralized applications building on Sei can build on top of the CLOB, and other Cosmos-based blockchains can leverage Sei's CLOB as a shared liquidity hub and create markets for any asset. 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In today’s fast-paced job market, Staffing agencies are becoming key players in the future of work. This is because as jobs change and new skills are constantly required, traditional hiring methods are rethought. According to the American Staff Association (ASA), nearly three million temporary and contract employees work for America’s staffing companies during an average week. It represents a broad trend toward flexible business processes. This shift is being driven by staffing companies offering innovative solutions that not only meet the immediate needs of staff but also prepare organizations for tomorrow’s challenges. Understanding the Evolving Role of Staffing Agencies Traditionally, they were seen as street saviors who jumped in whenever companies needed to fill vacancies quickly or there was a shortage of temporary workers, and today, their role has changed dramatically. Staffing agencies are now building relationships with companies where they help these organizations anticipate recruitment needs, manage talent pipelines, and staff the changing market dynamics. One of the most important functions of modern personnel agencies is the ability to provide exceptional talent. As technology advances, for example, the demand for specialized roles in AI, cybersecurity, and blockchain has increased. Staffing agencies have revolutionized internationally by expanding their search and recruitment but also by using sophisticated technology to better match the right candidate with the right job. How Staffing Agencies Enhance Workforce Flexibility? The concept of ‘working for life’ is becoming obsolete. Today’s workforce, especially millennials and Gen Z, value work-life balance, flexibility, and the opportunity to work on their own terms. According to the American Staffing Association (ASA), during the course of a year, America’s staffing companies hire over 14.5 million temporary and contract employees. Staffing agencies are facilitating this new employment arrangement by offering contract positions, part-time roles, and temporary work offering flexible staffing and recruitment services for both employers and employees. For businesses, the flexibility offered by staffing companies means they can increase or decrease their staff based on the demands of the business without being burdened with long-term commitments. This flexibility is important, especially in projects and events such as IT, where the scope and timeline of the project can change dramatically. Leveraging Global Talent In a globalized world, geographical boundaries no longer limit talent. Staffing agencies have become important links connecting global talent pools with local and international companies. This globalization is especially useful for areas where specific skills are lacking. By leveraging a broader pool of talent, companies can not only better address skills gaps but also increase diversity within their teams. Teams bring diverse perspectives and tend to be highly innovative and robust in problem-solving, qualities critical to competitive advantage in today’s marketplace. Navigating Regulatory Landscapes Employment laws and regulations can vary greatly from region to region. Working groups help companies navigate these complex legal issues, ensuring compliance and reducing the risk of legal challenges. Whether understanding new labor laws, managing contracts, or enforcing fair labor practices, staffing agencies provide a valuable service that protects both employer and employee. Impact of Technology on Employees Staffing solutions combining artificial intelligence and machine learning are transforming the hiring landscape. This technology simplifies, manages, and automates the recruitment process, as well as recruiters are able to focus more on engaging with prospective clients and understanding the needs of the companies they serve. Conclusion: The Role of Systemart in Shaping a Successful Future As we look to the future, the role of staffing agencies in successful businesses becomes more apparent. Systemart professionals stand out as leaders in the industry, providing tailored solutions that help companies remain agile, competitive, and forward-thinking. With a commitment to innovation and in-depth knowledge of market trends, Systemart is geared to not only help your business meet immediate employee needs but also provide a flexible workforce, and they are active and ready for tomorrow’s challenges. In partnership with Systemart, business In today’s fast-paced job market, staffing agencies are becoming key players in the future of work. In today’s fast-paced job market, Staffing agencies are becoming key players in the future of work. This is because as jobs change and new skills are constantly required, traditional hiring methods are rethought. According to the American Staff Association (ASA), nearly three million temporary and contract employees work for America’s staffing companies during an average week. three million It represents a broad trend toward flexible business processes. This shift is being driven by staffing companies offering innovative solutions that not only meet the immediate needs of staff but also prepare organizations for tomorrow’s challenges. Understanding the Evolving Role of Staffing Agencies Understanding the Evolving Role of Staffing Agencies Traditionally, they were seen as street saviors who jumped in whenever companies needed to fill vacancies quickly or there was a shortage of temporary workers, and today, their role has changed dramatically. Staffing agencies are now building relationships with companies where they help these organizations anticipate recruitment needs, manage talent pipelines, and staff the changing market dynamics. One of the most important functions of modern personnel agencies is the ability to provide exceptional talent. As technology advances, for example, the demand for specialized roles in AI, cybersecurity, and blockchain has increased. Staffing agencies have revolutionized internationally by expanding their search and recruitment but also by using sophisticated technology to better match the right candidate with the right job. How Staffing Agencies Enhance Workforce Flexibility? How Staffing Agencies Enhance Workforce Flexibility? The concept of ‘working for life’ is becoming obsolete. Today’s workforce, especially millennials and Gen Z, value work-life balance, flexibility, and the opportunity to work on their own terms. According to the American Staffing Association (ASA) , during the course of a year, America’s staffing companies hire over 14.5 million temporary and contract employees. American Staffing Association (ASA) 14.5 million Staffing agencies are facilitating this new employment arrangement by offering contract positions, part-time roles, and temporary work offering flexible staffing and recruitment services for both employers and employees. staffing and recruitment services For businesses, the flexibility offered by staffing companies means they can increase or decrease their staff based on the demands of the business without being burdened with long-term commitments. This flexibility is important, especially in projects and events such as IT, where the scope and timeline of the project can change dramatically. Leveraging Global Talent In a globalized world, geographical boundaries no longer limit talent. Staffing agencies have become important links connecting global talent pools with local and international companies. This globalization is especially useful for areas where specific skills are lacking. By leveraging a broader pool of talent, companies can not only better address skills gaps but also increase diversity within their teams. Teams bring diverse perspectives and tend to be highly innovative and robust in problem-solving, qualities critical to competitive advantage in today’s marketplace. Navigating Regulatory Landscapes Employment laws and regulations can vary greatly from region to region. Working groups help companies navigate these complex legal issues, ensuring compliance and reducing the risk of legal challenges. Whether understanding new labor laws, managing contracts, or enforcing fair labor practices, staffing agencies provide a valuable service that protects both employer and employee. Impact of Technology on Employees Staffing solutions combining artificial intelligence and machine learning are transforming the hiring landscape. This technology simplifies, manages, and automates the recruitment process, as well as recruiters are able to focus more on engaging with prospective clients and understanding the needs of the companies they serve. Conclusion: The Role of Systemart in Shaping a Successful Future As we look to the future, the role of staffing agencies in successful businesses becomes more apparent. Systemart professionals stand out as leaders in the industry, providing tailored solutions that help companies remain agile, competitive, and forward-thinking. With a commitment to innovation and in-depth knowledge of market trends, Systemart is geared to not only help your business meet immediate employee needs but also provide a flexible workforce, and they are active and ready for tomorrow’s challenges. In partnership with Systemart, business In today’s fast-paced job market, staffing agencies are becoming key players in the future of work.

The Role of Staffing Agencies: A Game Changer in the Future of Work

স্টাফিং এজেন্সিগুলির ভূমিকা: কাজের ভবিষ্যতের একটি গেম চেঞ্জার৷

Die Rolle von Personalagenturen: Ein Wendepunkt in der Zukunft der Arbeit

El papel de las agencias de empleo: un punto de inflexión en el futuro del trabajo

Le rôle des agences de placement de personnel : un facteur qui change la donne dans l'avenir du travail

स्टाफिंग एजेंसियों की भूमिका: कार्य के भविष्य में एक बड़ा परिवर्तन

人材派遣会社の役割: 仕事の未来を変えるゲームチェンジャー

채용 대행사의 역할: 미래 업무 방식의 판도를 바꾸는 역할

O papel das agências de recrutamento: uma virada de jogo no futuro do trabalho

Роль кадровых агентств: меняет правила игры в будущем сферы труда

İşe Alma Kurumlarının Rolü: İşin Geleceğinde Oyun Değiştirici

Vai trò của các cơ quan cung cấp nhân sự: Người thay đổi cuộc chơi trong tương lai của công việc

人力资源代理机构的作用：未来工作格局的改变者

About me and my experience Hi, I'm Alina. With nearly 9 years in design, my journey started much like many of my peers – from graphic and web design to my current role as a product designer. My focus lies in crafting and enhancing user interfaces, conducting tests, gathering components, and ultimately aligning business objectives with exceptional user experiences. Today, I want to share my insights on job hunting, hoping to benefit newcomers and seasoned professionals alike. Why UX/UI? What drew me to this path? Art captivated me from a young age, leading me to explore graphic design despite initially pursuing advertising. Through persistence and learning various design software, I gained entry into the field, starting in small web studios. As I delved deeper, my interest grew, and I expanded my skills through research and hands-on experience in diverse product teams. Now, I'm with Planneer5d, a global leader in interior design technology, serving millions worldwide. While my background in drawing sparked my interest, the UX/UI profession prioritizes engineering prowess over artistic talent. Why write about job hunting? Having navigated the job market myself, I understand the challenges and uncertainties that come with it. I want to share my experiences and insights to help others in the design community find their footing and secure rewarding opportunities in this ever-evolving field. Skill-set of a UX/UI designer in 2024 One of my biggest failings was that I initially entered the UX/UI market without the . And I always tried to research in a new place, either on my own or with the help of a research center, but I always had a great zeal to experience it in practice, to learn how it works. More often than not, a lot of jobs require this particular skill set. At interviews, they pick you, how good you are at qualitative and quantitative research, check what you know about it at all. And then, as a matter of fact, six months pass and you are not involved in research once, but there may be many reasons for this, let's leave it out, but the fact remains that you need to know how to research. skill of research So the first thing is the You need to know the base and have some experience in this. If we are talking about the base, you should definitely read about types of research – what types of research are exists, how it may be implemented, how it is prepared, how you should gather information, what you should do with it afterwards. It's likely that everything you'll find on the internets is the ideal research process and how a researcher should be. But that's not a bad thing. You know the base and this will help you further, try to do the research yourself if you don't have that experience: just take any product and start looking for bugs and problems in it, read reviews. Do this research work algorithm to understand it better. skill of the researcher. An unobvious skill, which for some reason is overlooked or missed by many people, is . The way you speak, how you present your work, tell about yourself, will decide whether you will be hired or not. In the work of a modern UX/UI designer you have to talk and negotiate a lot, in an accessible and understandable way. You will communicate not only with your team of designers and developers, but also participate in all processes, including communication with the business (because it is important to adapt the design to business needs and goals that both benefit the company and satisfy the user).The ability to ask the right questions and the ability to talk about solutions, to explain the value and effectiveness of their solutions is the most important quality, which converts not only into a monetary equivalent, but also into a credit of trust on the part of customers. communication is just as important. You should care more than anyone else. You should be directly captured by the flow of any product, you should be curious to understand how the registration form works, or how this TabBar appears, what kind of nesting it has, where the application goes after the user clicked "send". And also being intensely curious about at what point the user will interact with the product. You'll find this skill very much helps you find creative solutions to design or improve some feature or product. Curiosity is parallel to the desire for self-development: it is a skill of constant learning, learning new techniques, trends and technologies. Curiosity . Not obvious, but super important, this is about accessibility and inclusiveness. You need to understand, for example, how interfaces are designed for users with disabilities, what tools are used to test such products. Empathy skill Above was everything that concerns soft-skills. And, of course, I'll mention hard skills, without which there is nothing nowadays. Knowing how to work with As strange as it may sound, it really helps in work. Neural network can write a good UX-text, write a flow for you, gather a competitors' base, write a script for testing, etc. Here you need to know how to ask the right questions and formulate queries. . ChatGPT Skill in working with different illustration generators or KV (key visual) ( ). Midjourney / Stable Diffusion You need to be able to master tools such as and . This is very important in day-to-day work and helps a lot with planning and teamwork. Jira Confluence Being proficient in animation and prototyping tools will also help you have an edge over other candidates. There are some cool and handy tools out there right now, is a prototyping app, is a cool tool for 3D animations, and s for creating 2D animations. I recommend you to explore them as well, they can come in handy in your work: both in product presentation and for creating any interface animations. ProtoPie Spline i Lottie Animation Know, understand and love web builders , , . Webflow Tilda Wix You, as a designer, should understand the principles of working in different frameworks. Such as , and others. Not to forget the – it's important for interface design.
Perhaps that's all I'd like to highlight and recommend to learn. Design thinking , Jobs To Be Done Lean UX laws of UX Your portfolio: tips and platforms The question about platforms for posting your portfolio is an important one, but honestly, I don't follow it myself as much as I probably should. Because I just can't find the time to do it, or I think - "nothing, I'll put it off for a better time". However, getting back to the question - it's ideal if you keep a diary, write a note - anything - every time you are faced with any task at work! This will help you then, in the future, to tell and describe the process of work and to identify from this task the positives and what you learned. But it's not only good for portfolios, it's also good for behavioral interviews. Because if you break down each of your work tasks, you can answer any behavioral question. Try to keep a diary or notes with detailed descriptions. Make wireframes of your awesome interesting cases every six months. And every year, try to pick and choose a new case study from your notes and wireframes.
Your portfolio should not contain 2 million works: here I worked in a printing house, and here I drew a banner, No, we are UX/UI designers, which means, well, maximum 5 cases you need to keep in your portfolio. And, of course, pay attention to the fact that we have to tell about the case in detail, namely: tell what you did, not the team; what the problem was; what framework was used or how you did your research (competitor analysis, survey, etc.) and demonstrate it; show low-frequency wireframes, diagrams, flowcharts, and the rest of the artifacts; talk about the results and figures. The best thing is to keep your portfolio on your own website. This can easily be done on Tilda or on Webflow - also a good tool. It's also very common nowadays for Senior level designers to use . Notion I don't recommend storing in , in . and especially not on Recruiters and the hiring team leader don't have time to go through long uploaded documents and large portfolios with more text. They only have an hour to review 50 portfolios. The rest of the time this team leader spends in calls. So make sure that your portfolio is as readable as possible, so that a quick glance will help recruitment understand everything. Figma pdf google disk. Business needs for good UX/UI designers and secrets of job search Answering the question about which businesses from which areas are now more likely to face a shortage of good UX/UI designers, I would say it's the segments of government organizations and industry. More often than not, they are always bad at UX/UI. But! I wouldn't advise you to look for a position there, because there are too complex and entrenched processes that will have to be shifted before something new is introduced. Let's imagine you're looking for a job in Poland, try putting that region on LinkedIn, see what companies are hiring designers, or what companies even exist/base themselves in the region you're looking for a job in. Try (remember your letter should be concise and simple so the recruiter has time to read it), look for internships. writing directly to the team or recruiter I also recommend paying attention to resources such as – I like it a lot. Also, of course, and, of course, there are various Telegram channels, where they also publish interesting vacancies, you should keep an eye on them. getmatch Otta I also recommend you to pay attention to these resources wellfound mind the product we work remotely Interviews: preparing I've had 40 interviews in my career, or even more. And that's because either the company didn't suit me, or I wasn't professionally prepared for such work. The most memorable was the first one. I was applying for a job with the guys who design road signs, and I really wanted to start somewhere, somewhere to work. I knew Photoshop and Illustrator by then. Anyway, they were asking me questions about my experience, what I was doing. And I was just showing my sister's work and some of my own to make me look more confident and professional. In general, I showed my sister's work - websites (I had no idea then how they were made), and my graphics. And when they started asking me very deeply about the website, I was confused. This is the most memorable, because you should not lie, do not attribute someone else's work to yourself. If you have no experience in something, try to do a project on your own, do some research, find some nuances in the product, propose a better solution. Test it. That way you will understand better what the job is all about, and you won't have to lie to your employer. As soon as I entered the design market, I had no idea that you should and can prepare for interviews. And there is so much information out there to help you interview well and get the offer you want. So at first I was very afraid of interviews, almost to the point of panic attacks. But then I started to study my mistakes, read articles, collect feedback from recruiters, write myself down. And everything got better, and now I am more confident in such situations. What is necessary and important: You've probably heard about it a hundred times. Check out the company blog, read articles, look for company representatives speaking at conferences, meetups, maybe they run some kind of their own Telegram channel. Read SEO interviews, look into the company's values and culture. You might even be able to find your teamleader and study their profile as well. Try to find reviews about the company, talk to someone who is already working. This is a stage, just like in our profession - a stage of analyzing and searching. Research a company. First, practice a short self-presentation: you don't have to answer the question "tell us a little about yourself" with a 40-minute presentation! Try to keep it to 3 minutes. Here you should tell about your recent and previous experience, and highlight important facts that just meshes with the company's wishes. If the company is looking for a designer with research skills and animation skills, try to mention that, tell them that you've been able to get in touch with that. I would also emphasize three points: a) talk briefly about, for example, the last 3-5 years of work (depends on experience) + accomplishments there; b) update your current experience + achievements there as well; c) describe your career goals, and why you are in search. Prepare a presentation about yourself. about each case study. Tip: Try to write down questions that come up in the interview about your cases so that you can cover them immediately at other interviews in the future. Prepare a portfolio and practice talking , they come in many forms. There are platforms with coaching for such questions. Practice behavioral questions you'd like to ask the company, the team, and maybe even the SEO. Think about what questions Helpful resources for coaching behavioral questions: biginterview pramp interview-warmup questions-to-ask article Interviews: how it goes First there is the You talk to the recruiter, he asks you simple questions: who you are, why you are looking for a job, your experience. The recruiter's task at this point is to find out how adequate you are, how you conduct the dialog, whether the company's wishes coincide with your skills. Usually the duration is no more than 30 minutes. screening process. Further, if everything is good and you fit all the parameters, the recruiter already passes the information about you to the team leader, and you are assigned a meeting with the team. can take up to a week. The waiting period The next stage is with the team. Here they will ask about your experience: on specific cases you will need to tell what you did, perhaps they will ask you to show a figma to understand how you maintain your workplace. Also at this stage they may ask you to solve some task. For example, they will ask you to show the registration process, this is where your approach to work is assessed. may also be asked: such as, tell us about a time when you had a very tight deadline / tell us about a colleague with whom you couldn't agree / tell us about a project where you made a mistake and it was critical. You need to answer honestly - this question is necessary to understand how you behave in stressful situations, how you cope with difficulties, how you organize your working time, whether you can prioritize tasks and whether you are an effective time manager. This is where it's time to get your notes sorted out. At the end of the interview, you may be asked to complete a test task. This stage can take from one to one and a half hours. a technical interview Behavioral questions The last stage could be or a meeting with the SEO. To summarize, there can be three or four stages, it all depends on the processes in the company. a defense of your test case solution Another common question is "why chose us" and "why are you looking for a job". Answer these two questions honestly. To answer the first one, a recertification will help you, highlight something important to you - the company culture or work processes - anything that interests you! Don't, of course, say you're only here for the money. Tell them why you decided to change jobs. The most common answer is that it is a need for professional growth, for example, you can answer like this: I am very grateful to company X, I have learned a lot, but I feel that I need growth, the tasks have become routine and simple for me, so I decided to go on a search. I would also like to add that there are several techniques for answering behavioral questions. For example one of the famous techniques is STAR: - (challange) a company wanted to increase the number of subscriptions with /through our service /situation - I needed to create a marketing plan that would help me achieve the goal. /task - action, I decided to use 3 different ones at the same time, we planned a few different family events and ran them /action - not only did we reach our goal, but we still made a 60% revenue. /result Read more about STAR here By the way, I've never been asked about "what do you see yourself as in the next 5 years." That's because it's really quite a complicated question, we live in such an unusually complicated time, I never thought I would be in emigration for two years, for example, so if you do get asked that question, try to think about your growth beforehand – how you see it: linear or vertical. Test tasks How to treat it and whether it are worth doing? No matter how many different managers I listen to, and no matter how many interviews I go on, no one has one, unified opinion. For some, it's enough to look at your work and talk about case studies. And someone needs to see how a candidate handles a test assignment. Therefore, if you are asked to do a test - agree if you are interested in the company and would really like to get there. On the test they look at your work process, your layout design, mastery of components, mastery of research skills and presentation skills. The better you do on the test, the better chance you have of grabbing that coveted spot, so be sure to reserch, show your workflow, surveys, artifacts. Also pay attention to your text! Don't make mistakes and typos in test jobs, ask questions if something is not clear. Read a helpful article about test-taking assignments What questions should I ask my employer? It is very important to think in advance about what you would like to learn about the company or the work process and tasks. In its turn, the company records how interested you are, and it's strange that you can't care about anything at all, try to compare it with your previous experience - what you cared about there, try to ask the recruiter this question somehow correctly. What are the company's/team's objectives for the next six months? What is the approval process for the new feature / workflow? What platforms will I have to work with? And what is the number of users? How is the research / do you have your own research center? What are your goals for the new candidate. What does he/she have to do to pass the probationary period? What skills are important to you in a candidate? And why exactly did you choose this company, why do you like it, and what, perhaps, are the disadvantages? I've also put together some helpful articles for you that will help you not to think about what questions you would ask your employer: unique-questions-to-ask-employers questions-you-should-be-asking Thank you for reading this article, use my advice, put it into practice and share your experience! I hope it was useful  💛🩷🩵

Coveted Careers: Mastering the Art of Securing Top UI/UX Design Roles in 2024

লোভনীয় ক্যারিয়ার: 2024 সালে শীর্ষ UI/UX ডিজাইনের ভূমিকা সুরক্ষিত করার শিল্পে দক্ষতা অর্জন

Begehrte Karrieren: Meistern Sie die Kunst, sich im Jahr 2024 Spitzenpositionen im UI/UX-Design zu sichern

Carreras codiciadas: dominar el arte de asegurar los mejores roles de diseño de UI/UX en 2024

Carrières convoitées : maîtriser l’art d’obtenir les meilleurs rôles de conception UI/UX en 2024

प्रतिष्ठित करियर: 2024 में शीर्ष यूआई/यूएक्स डिज़ाइन भूमिकाएँ सुरक्षित करने की कला में महारत हासिल करना

切望されるキャリア: 2024 年にトップの UI/UX デザイン職を獲得するための技術を習得する

탐나는 직업: 2024년 최고의 UI/UX 디자인 역할을 확보하는 기술 습득

Carreiras cobiçadas: dominando a arte de garantir as principais funções de UI/UX Design em 2024

Желанная карьера: овладение искусством поиска лучших должностей в сфере UI/UX-дизайнеров в 2024 году

Beğenilen Kariyerler: 2024'te En İyi UI/UX Tasarım Rollerini Sağlama Sanatında Ustalaşmak

Những nghề nghiệp đáng mơ ước: Nắm vững nghệ thuật đảm bảo các vai trò thiết kế UI/UX hàng đầu vào năm 2024

令人垂涎的职业：掌握 2024 年获得顶级 UI/UX 设计职位的艺术

Systems Interoperability Types: The Conclusion to Our Tertiary Study

What Skills Will Help You Become a Good Development Team Leader?

কোন দক্ষতা আপনাকে একজন ভালো ডেভেলপমেন্ট টিম লিডার হতে সাহায্য করবে?

Welche Fähigkeiten helfen Ihnen, ein guter Entwicklungsteamleiter zu werden?

¿Qué habilidades le ayudarán a convertirse en un buen líder de equipo de desarrollo?

Quelles compétences vous aideront à devenir un bon chef d’équipe de développement ?

कौन से कौशल आपको एक अच्छा विकास टीम लीडर बनने में मदद करेंगे?

優れた開発チームのリーダーになるために役立つスキルは何ですか?

좋은 개발 팀 리더가 되는 데 어떤 기술이 도움이 될까요?

Que habilidades o ajudarão a se tornar um bom líder de equipe de desenvolvimento?

Какие навыки помогут вам стать хорошим руководителем группы разработки?

İyi Bir Geliştirme Ekibi Lideri Olmanıza Hangi Beceriler Yardımcı Olur?

Những kỹ năng nào sẽ giúp bạn trở thành một Trưởng nhóm phát triển giỏi?

哪些技能可以帮助您成为一名优秀的开发团队领导者？

It seems that everything we have been doing for the last four years is talking about the elusive ‘new normal.’ First, it was the COVID-19 pandemic, then, it was our global shift to the remote mode, after that it was living in a world filled with economic and political uncertainty. And here we are, talking about it once again. What is the ‘new normal’ for 2024, and will we be able to overcome everything the year will throw at us? AI gains even more importance. In 2023, AI occupied the headlines in almost every media. And we thought the craze would die down in a few short months. As time goes on, we see AI becoming not only THE technology to watch but also feeling cozier and cozier in our minds and our work processes. Today, it is used to , , and even (the last one is appalling). Nevertheless, AI is seeping into our everyday lives more, and even the laggards (it’s a word now) of laggards can no longer ignore its impact on the world. decipher ancient scrolls enhance student creativity cheat people out of their money I think 2024 will become the year of not only further AI development but also AI regulation. The process in the US and EU, so more countries are likely to follow suit. has already started Low well-being rates According to the recent report by , “The percentage of Americans who evaluate their lives well enough to be considered "thriving" on Gallup’s Life Evaluation Index averaged a subdued 52.1% in 2023, higher than only the Great Recession era reading in 2008-2009 (50.2%) and the first year of the COVID-19 pandemic in 2020 (50.1%). [...] Between 2015 and 2019, and in 2021, more than 55% were thriving.” Gallup Economic, political, and ecological downturns have, sadly, become a part of our everyday lives. In fact, sometimes it seems our world is on fire, and there is nothing we can do about it. No wonder our mental health and well-being rates are so low. As bad as it may seem, there are things I find to be the most helpful when I am feeling down: Communication — even a simple work call can be therapeutic because it can help us switch our attention to something other than our personal state. Books — ever since childhood, I have considered books one of the best ways, if not to escape, than to enhance our reality. Reading is one of my favorite hobbies, and it helps me relax and almost forget about everything going on around me. Sports — whatever it may be, running, squash, yoga, or sports- has been a part of my personal and even work life. Scientific also supports this approach. It has been proven that sport improves mental health, decreases the rates of ‘psychological ill-being’, and improves interpersonal communication. Win-win. data Doing something for myself — whether it is traveling, studying, going to the gym, or watching a movie when I have the time, I have found dedicating at least 30 minutes a day to my personal needs fills me up with energy and brings me the inspiration I need to face any challenge that the world might throw at us. 2024 started off with low well-being rates, and we should do everything we can to bring the numbers up and meet 2025 on a high note. Teams will no longer tolerate toxic leaders “We know our worth” — this is the attitude professionals have been coming to for several years. In 2024, leaders who have been displaying a tendency to be may be in for an unpleasant surprise. Even despite all the , teams no longer want to put up with toxicity, micromanagement, arrogance, irritability, and bullying from their managers and leaders. Our world is filled with possibilities and, for that matter, vacancies for professionals in different fields and with different skill sets. toxic tech layoffs 2024 is the year for managers to stop perceiving their toxicity as something they should hold on to. It is also nothing to be proud of, so business leaders need to either adjust their attitude or watch their teams slip through their fingers. Burn- and rust-out rates are off the charts Toxic managers, the lack of stability, constant technological disruptions, and low mental health rates have led us to extremely high rates of and out. If 2024 numbers remain as high as they were in 2023 or, even worse, will keep on increasing, we will end up with the entire global workforce unable to perform, grow, develop their skills, and bring new and modern solutions to the table. burning rusting Leaders have to address the trend this year and make necessary adjustments to make sure their teams have all the conditions they need to perform well and keep their mental health in check. 2024 has brought new challenges for us to address. But if my years of working in the tech industry taught me anything, it is that we usually come to the right decision, overcome the challenges posed ahead of us, and come out even more capable. That is one of my goals for this year.

What is the 'New Normal' for 2024

This paper is available on arxiv under CC BY-SA 4.0 DEED license. Authors: (1) Mathias-Felipe de-Lima-Santos, Faculty of Humanities, University of Amsterdam, Institute of Science and Technology, Federal University of São Paulo; (2) Wilson Ceron, Institute of Science and Technology, Federal University of São Paulo. Table of Links Abstract & Introduction Data and Methods Results Discussion and Conclusions Funding and References Funding This project was partially funded by the University of Amsterdam’s RPA Human(e) AI and by the European Union’s Horizon 2020 research and innovation programs No 951911 (AI4Media). References (1) Sunstein, C. R. #Republic: Divided Democracy in the Age of Social Media; Princeton University Press: Princeton, New Jersey, 2017. (2) Garimella, K.; De Francisci Morales, G.; Gionis, A.; Mathioudakis, M. Political Discourse on Social Media. In Proceedings of the 2018 World Wide Web Conference on World Wide Web - WWW ’18; ACM Press: New York, New York, USA, 2018; Vol. 2, pp 913–922. https://doi.org/10.1145/3178876.3186139. (3) Del Vicario, M.; Bessi, A.; Zollo, F.; Petroni, F.; Scala, A.; Caldarelli, G.; Stanley, H. E.; Quattrociocchi, W. The Spreading of Misinformation Online. Proc. Natl. Acad. Sci. 2016, 113 (3), 554–559. https://doi.org/10.1073/pnas.1517441113. (4) Garrett, R. K. Echo Chambers Online?: Politically Motivated Selective Exposure among Internet News Users. J. Comput. Commun. 2009, 14 (2), 265–285. https://doi.org/10.1111/j.1083- 6101.2009.01440.x. (5) Nickerson, R. S. Confirmation Bias: A Ubiquitous Phenomenon in Many Guises. Rev. Gen. Psychol. 1998, 2 (2), 175–220. https://doi.org/10.1037/1089-2680.2.2.175. (6) Biehl, J. A Political Economy of Pharmaceuticals. Will to Live 2021, 18 (1), 10–13. https://doi.org/10.2307/j.ctv1wmz48h.5. (7) Allcott, H.; Gentzkow, M. Social Media and Fake News in the 2016 Election. J. Econ. Perspect. 2017, 31 (2), 211–236. https://doi.org/10.1257/jep.31.2.211. (8) Bennett, W. L.; Livingston, S. The Disinformation Order: Disruptive Communication and the Decline of Democratic Institutions. Eur. J. Commun. 2018, 33 (2), 122–139. https://doi.org/10.1177/0267323118760317. (9) Giglietto, F.; Righetti, N.; Rossi, L.; Marino, G. It Takes a Village to Manipulate the Media: Coordinated Link Sharing Behavior during 2018 and 2019 Italian Elections. Inf. Commun. Soc. 2020, 23 (6), 867–891. https://doi.org/10.1080/1369118X.2020.1739732. (10) Farkas, J.; Schou, J. Fake News as a Floating Signifier: Hegemony, Antagonism and the Politics of Falsehood. Javnost 2018, 25 (3), 298–314. https://doi.org/10.1080/13183222.2018.1463047. (11) Wardle, C. The Need for Smarter Definitions and Practical, Timely Empirical Research on Information Disorder. Digit. Journal. 2018, 6 (8), 951–963. https://doi.org/10.1080/21670811.2018.1502047. (12) Abramowitz, S.; McKune, S. L.; Fallah, M.; Monger, J.; Tehoungue, K.; Omidian, P. A. The Opposite of Denial: Social Learning at the Onset of the Ebola Emergency in Liberia. J. Health Commun. 2017, 22 (sup1), 59–65. https://doi.org/10.1080/10810730.2016.1209599. (13) Guidry, J. P. D.; Jin, Y.; Orr, C. A.; Messner, M.; Meganck, S. Ebola on Instagram and Twitter: How Health Organizations Address the Health Crisis in Their Social Media Engagement. Public Relat. Rev. 2017, 43 (3), 477–486. https://doi.org/10.1016/j.pubrev.2017.04.009. (14) Guidry, J. P. D.; Meganck, S. L.; Perrin, P. B.; Messner, M.; Lovari, A.; Carlyle, K. E. #Ebola: Tweeting and Pinning an Epidemic. Atl. J. Commun. 2021, 29 (2), 79–92. https://doi.org/10.1080/15456870.2019.1707202. (15) Smallman, S. Whom Do You Trust? Doubt and Conspiracy Theories in the 2009 Influenza Pandemic. J. Int. Glob. Stud. 2015, 6 (2), 1–24. (16) Wagner-Egger, P.; Bangerter, A.; Gilles, I.; Green, E.; Rigaud, D.; Krings, F.; Staerklé, C.; Clémence, A. Lay Perceptions of Collectives at the Outbreak of the H1n1 Epidemic: Heroes, Villains and Victims. Public Underst. Sci. 2011, 20 (4), 461–476. https://doi.org/10.1177/0963662510393605. (17) Arif, N.; Al-Jefri, M.; Bizzi, I. H.; Perano, G. B.; Goldman, M.; Haq, I.; Chua, K. L.; Mengozzi, M.; Neunez, M.; Smith, H.; Ghezzi, P. Fake News or Weak Science? Visibility and Characterization of Antivaccine Webpages Returned by Google in Different Languages and Countries. Front. Immunol. 2018, 9 (JUN), 1215. https://doi.org/10.3389/fimmu.2018.01215. (18) Dubé, E.; Vivion, M.; MacDonald, N. E. Vaccine Hesitancy, Vaccine Refusal and the AntiVaccine Movement: Influence, Impact and Implications. Expert Rev. Vaccines 2014, 14 (1), 99– 117. https://doi.org/10.1586/14760584.2015.964212. (19) West, J. D.; Bergstrom, C. T. Misinformation in and about Science. Proc. Natl. Acad. Sci. U. S. A. 2021, 118 (15), e1912444117. https://doi.org/10.1073/pnas.1912444117. (20) Hornsey, M. J.; Harris, E. A.; Fielding, K. S. The Psychological Roots of Anti-Vaccination Attitudes: A 24-Nation Investigation. Heal. Psychol. 2018, 37 (4), 307–315. https://doi.org/10.1037/hea0000586. (21) Ceron, W.; De-Lima-Santos, M.-F.; Quiles, M. G. Fake News Agenda in the Era of COVID-19: Identifying Trends through Fact-Checking Content. Online Soc. Networks Media 2021, 21, 100116. https://doi.org/10.1016/j.osnem.2020.100116. (22) Ceron, W.; Sanseverino, G. G.; De-Lima-Santos, M.-F.; Quiles, M. G. COVID-19 Fake News Diffusion across Latin America. Soc. Netw. Anal. Min. 2021, 11 (1), 47. https://doi.org/10.1007/s13278-021-00753-z. (23) Chadwick, A.; Kaiser, J.; Vaccari, C.; Freeman, D.; Lambe, S.; Loe, B. S.; Vanderslott, S.; Lewandowsky, S.; Conroy, M.; Ross, A. R. N.; Innocenti, S.; Pollard, A. J.; Waite, F.; Larkin, M.; Rosebrock, L.; Jenner, L.; McShane, H.; Giubilini, A.; Petit, A.; Yu, L. M. Online Social Endorsement and Covid-19 Vaccine Hesitancy in the United Kingdom. Soc. Media Soc. 2021, 7 (2), 205630512110088. https://doi.org/10.1177/20563051211008817. (24) Monari, A. C. P.; Sacramento, I. A “Vacina Chinesa de João Doria”: A Influência Da Disputa Política-Ideológica Na Desinformação Sobre a Vacinação Contra a Covid-19. Rev. Mídia e Cotid. 2021, 15 (3), 125–143. (25) Bode, L.; Vraga, E. The Swiss Cheese Model for Mitigating Online Misinformation. Bull. At. Sci. 2021, 77 (3), 129–133. https://doi.org/10.1080/00963402.2021.1912170. (26) Gera, S.; Sinha, A. C-ANN: A Deep Leaning Model for Detecting Black-Marketed Colluders in Twitter Social Network. Neural Comput. Appl. 2022, 34 (18), 15113–15127. https://doi.org/10.1007/s00521-021-06756-3. (27) Gleicher, N. Coordinated inauthentic behavior explained https://about.fb.com/news/2018/12/inside-feed-coordinated-inauthenticbehavior/%0Ahttps://newsroom.fb.com/news/2018/12/inside-feed-coordinated-inauthenticbehavior/ (accessed Oct 11, 2021). (28) Broniatowski, D. A. Towards Statistical Foundations for Detecting Coordinated Inauthentic Behavior on Facebook; Washington, DC, 2021. (29) Freelon, D.; Wells, C. Disinformation as Political Communication. Polit. Commun. 2020, 37 (2), 145–156. https://doi.org/10.1080/10584609.2020.1723755. (30) Keller, F. B.; Schoch, D.; Stier, S.; Yang, J. H. Political Astroturfing on Twitter: How to Coordinate a Disinformation Campaign. Polit. Commun. 2020, 37 (2), 256–280. https://doi.org/10.1080/10584609.2019.1661888. (31) Yang, K. C.; Pierri, F.; Hui, P. M.; Axelrod, D.; Torres-Lugo, C.; Bryden, J.; Menczer, F. The COVID-19 Infodemic: Twitter versus Facebook. Big Data Soc. 2021, 8 (1). https://doi.org/10.1177/20539517211013861. (32) Kim, Y.; Song, D.; Lee, Y. J. #Antivaccination on Instagram: A Computational Analysis of Hashtag Activism through Photos and Public Responses. Int. J. Environ. Res. Public Health 2020, 17 (20), 1–20. . https://doi.org/10.3390/ijerph17207550 (33) Möller, J. Filter Bubbles and Digital Echo Chambers. In The Routledge Companion to Media
Disinformation and Populism; Tumber, H., Waisbord, S., Eds.; Routledge: London, 2021; pp 92–
100. . https://doi.org/10.4324/9781003004431-10 (34) Dahlgren, P. The Internet, Public Spheres, and Political Communication: Dispersion and
Deliberation. Polit. Commun. 2005, 22 (2), 147–162. . https://doi.org/10.1080/10584600590933160 (35) Belair-Gagnon, V.; Nelson, J. L.; Lewis, S. C. Audience Engagement, Reciprocity, and the
Pursuit of Community Connectedness in Public Media Journalism. Journal. Pract. 2019, 13 (5),
558–575. .
(36) Benkler, Y. The Wealth of Networks; Yale University Press: New York, 2006. https://doi.org/10.1080/17512786.2018.1542975 (37) McPherson, M.; Smith-Lovin, L.; Cook, J. M. Birds of a Feather: Homophily in Social
Networks. Annu. Rev. Sociol. 2001, 27 (1), 415–444. . https://doi.org/10.1146/annurev.soc.27.1.415 (38) Terren, L.; Borge, R. Echo Chambers on Social Media: A Systematic Review of the Literature.
Rev. Commun. Res. 2021, 9 (May), 1–39. . https://doi.org/10.12840/ISSN.2255-4165.028 (39) Gt Walker, P.; Whittaker, C.; Watson, O.; Baguelin, M.; Ainslie, K. E. C.; Bhatia, S.; Bhatt, S.;
Boonyasiri, A.; Boyd, O.; Cattarino, L.; Cucunubá, Z.; Cuomo-Dannenburg, G.; Dighe, A.;
Donnelly, C. A.; Dorigatti, I.; Van Elsland, S.; Fitzjohn, R.; Flaxman, S.; Fu, H.; Gaythorpe, K.;
Geidelberg, L.; Grassly, N.; Green, W.; Hamlet, A.; Hauck, K.; Haw, D.; Hayes, S.; Hinsley, W.;
Imai, N.; Jorgensen, D.; Knock, E.; Laydon, D.; Mishra, S.; Nedjati-Gilani, G.; Okell, L. C.; Riley,
S.; Thompson, H.; Unwin, J.; Verity, R.; Vollmer, M.; Walters, C.; Wang, W.; Wang, Y.;
Winskill, P.; Xi, X.; Ferguson, N. M.; Ghani, A. C. The Global Impact of COVID-19 and Strategies
for Mitigation and Suppression; 2020. (40) Bruns, A. Echo Chambers? Filter Bubbles? The Misleading Metaphors That Obscure the Real
Problem. In Hate Speech and Polarization in Participatory Society; Pérez-Escolar, M., NogueraVivo, J. M., Eds.; Routledge: London, 2021; pp 33–48. 4. https://doi.org/10.4324/9781003109891- (41) Flaxman, S.; Goel, S.; Rao, J. M. Filter Bubbles, Echo Chambers, and Online News
Consumption. Public Opin. Q. 2016, 80 (Specialissue1), 298–320. . https://doi.org/10.1093/poq/nfw006 (42) Bakshy, E.; Messing, S.; Adamic, L. A. Exposure to Ideologically Diverse News and Opinion
on Facebook. Science (80-. ). 2015, 348 (6239), 1130–1132. . https://doi.org/10.1126/science.aaa1160 (43) Bright, J. Explaining the Emergence of Political Fragmentation on Social Media: The Role of
Ideology and Extremism. J. Comput. Commun. 2018, 23 (1), 17–33. . https://doi.org/10.1093/JCMC/ZMX002 (44) Eady, G.; Nagler, J.; Guess, A.; Zilinsky, J.; Tucker, J. A. How Many People Live in Political
Bubbles on Social Media? Evidence From Linked Survey and Twitter Data. SAGE Open 2019,
9 (1). . https://doi.org/10.1177/2158244019832705 (45) Garimella, K.; Morales, G. D. F.; Gionis, A.; Mathioudakis, M. Quantifying Controversy on
Social Media. ACM Trans. Soc. Comput. 2018, 1 (1), 1–27. . https://doi.org/10.1145/3140565 (46) Cinelli, M.; De Francisci Morales, G.; Galeazzi, A.; Quattrociocchi, W.; Starnini, M. The Echo
Chamber Effect on Social Media. Proc. Natl. Acad. Sci. 2021, 118 (9), e2023301118. . https://doi.org/10.1073/pnas.2023301118 (47) Arguedas, A. R.; Robertson, C. T.; Fletcher, R.; Nielsen, R. K. Echo Chambers, Filter Bubbles, and
Polarisation: A Literature Review; Oxford, 2022. (48) Bucher, T.; Helmond, A. The Affordances of Social Media Platforms. In The SAGE Handbook of
Social Media; Burgess, J., Marwick, A., Poell, T., Eds.; SAGE Publications Ltd: 1 Oliver’s Yard,
55 City Road London EC1Y 1SP, 2018; pp 233–253. . https://doi.org/10.4135/9781473984066.n14 (49) Barberá, P. How Social Media Reduces Mass Political Polarization. Evidence from Germany, Spain, and the U.S; 2015. (50) van der Linden, S. Misinformation: Susceptibility, Spread, and Interventions to Immunize the Public. Nat. Med. 2022, 28 (3), 460–467. . https://doi.org/10.1038/s41591-022-01713-6 (51) Righetti, N. Four Years of Fake News: A Quantitative Analysis of the Scientific Literature. First Monday 2021. https://doi.org/10.5210/fm.v26i7.11645. (52) Tandoc, E. C.; Lim, Z. W.; Ling, R. Defining “Fake News”: A Typology of Scholarly Definitions. Digit. Journal. 2018, 6 (2), 137–153. https://doi.org/10.1080/21670811.2017.1360143. (53) Chang, K.-C.; Menczer, F. How many bots are on Twitter? The question is tough to answer — and misses the point https://www.niemanlab.org/2022/05/how-many-bots-are-on-twitterthe-question-is-tough-to-answer-and-misses-the-point/ (accessed Sep 1, 2022). (54) Giglietto, F.; Righetti, N.; Marino, G. Understanding Coordinated and Inauthentic Link Sharing Behavior on Facebook in the Run-up to 2018 General Election and 2019 European Election in Italy; SocArXiv, 2019. https://doi.org/10.31235/osf.io/3jteh. (55) Giglietto, F.; Iannelli, L.; Rossi, L.; Valeriani, A.; Righetti, N.; Carabini, F.; Marino, G.; Usai, S.; Zurovac, E. Mapping Italian News Media Political Coverage in the Lead-Up of 2018 General Election. SSRN Electron. J. 2018. https://doi.org/10.2139/ssrn.3179930. (56) Giglietto, F.; Righetti, N.; Rossi, L.; Marino, G. Coordinated Link Sharing Behavior as a Signal to Surface Sources of Problematic Information on Facebook. ACM Int. Conf. Proceeding Ser. 2020, 20, 85–91. https://doi.org/10.1145/3400806.3400817. (57) Varol, O.; Ferrara, E.; Davis, C. A.; Menczer, F.; Flammini, A. Online Human-Bot Interactions: Detection, Estimation, and Characterization. Proc. 11th Int. Conf. Web Soc. Media, ICWSM 2017 2017, 280–289. (58) Khaund, T.; Kirdemir, B.; Agarwal, N.; Liu, H.; Morstatter, F. Social Bots and Their Coordination During Online Campaigns: A Survey. IEEE Trans. Comput. Soc. Syst. 2022, 9 (2), 530–545. https://doi.org/10.1109/TCSS.2021.3103515. (59) Dang, S.; Paul, K.; Chmielewski, D. Do spam bots really comprise under 5% of Twitter users? Elon Musk wants to know | Reuters https://www.reuters.com/technology/do-spam-botsreally-comprise-under-5-twitter-users-elon-musk-wants-know-2022-05-13/ (accessed Sep 1, 2022). (60) Luceri, L.; Deb, A.; Giordano, S.; Ferrara, E. Evolution of Bot and Human Behavior during Elections. First Monday 2019, 24 (9). https://doi.org/10.5210/fm.v24i9.10213. (61) Bugra Torusdag, M.; Kutlu, M.; Selcuk, A. A. Are We Secure from Bots? Investigating Vulnerabilities of Botometer. 5th Int. Conf. Comput. Sci. Eng. UBMK 2020 2020, 343–348. https://doi.org/10.1109/UBMK50275.2020.9219433. (62) Balestrucci, A. How Many Bots Are You Following? In CEUR Workshop Proceedings; Ancona; Italy, 2020; pp 47–59. (63) Bello, B. S.; Heckel, R.; Minku, L. Reverse Engineering the Behaviour of Twitter Bots. 2018 5th Int. Conf. Soc. Networks Anal. Manag. Secur. SNAMS 2018 2018, 27–34. https://doi.org/10.1109/SNAMS.2018.8554675. (64) Akyon, F. C.; Esat Kalfaoglu, M. Instagram Fake and Automated Account Detection. In Proceedings - 2019 Innovations in Intelligent Systems and Applications Conference, ASYU 2019; IEEE, 2019; pp 1–7. https://doi.org/10.1109/ASYU48272.2019.8946437. (65) Cresci, S. A Decade of Social Bot Detection. Commun. ACM 2020, 63 (10), 72–83. https://doi.org/10.1145/3409116. (66) Al-Khateeb, S.; Agarwal, N. Examining Botnet Behaviors for Propaganda Dissemination: A Case Study of ISIL’s Beheading Videos-Based Propaganda. In Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015; IEEE, 2016; pp 51–57. https://doi.org/10.1109/ICDMW.2015.41. (67) Islam, A. K. M. N.; Laato, S.; Talukder, S.; Sutinen, E. Misinformation Sharing and Social Media Fatigue during COVID-19: An Affordance and Cognitive Load Perspective. Technol. Forecast. Soc. Change 2020, 159, 120201. https://doi.org/10.1016/j.techfore.2020.120201. (68) Törnberg, P. Echo Chambers and Viral Misinformation: Modeling Fake News as Complex Contagion. PLoS One 2018, 13 (9), 1–21. https://doi.org/10.1371/journal.pone.0203958. (69) IFCN. International Fact-Checking Network – Poynter https://www.poynter.org/ifcn/ (accessed Jul 27, 2020). (70) Bruns, A.; Harrington, S.; Hurcombe, E. ‘Corona? 5G? Or Both?’: The Dynamics of COVID-19/5G Conspiracy Theories on Facebook. Media Int. Aust. 2020, 177 (1), 12–29. https://doi.org/10.1177/1329878X20946113. (71) de-Lima-Santos, M.-F.; Kooli, A. Instagrammable Data: Using Visuals to Showcase More Than Numbers on AJ Labs Instagram Page. Int. J. Commun. 2022, 16, 2821–2842. https://doi.org/1932–8036/20220005. (72) Reuters. Facebook removes dozens of vaccine misinformation “superspreaders” https://www.reuters.com/technology/facebook-removes-dozens-vaccine-misinformationsuperspreaders-2021-08-18/ (accessed Oct 11, 2021). (73) Bastian, M.; Heymann, S.; Jacomy, M. Gephi: An Open Source Software for Exploring and Manipulating Networks. Icwsm 2009. (74) Blondel, V. D.; Guillaume, J. L.; Lambiotte, R.; Lefebvre, E. Fast Unfolding of Communities in Large Networks. J. Stat. Mech. Theory Exp. 2008, 2008 (10), 10008. https://doi.org/10.1088/1742- 5468/2008/10/P10008. (75) Fortunato, S. Community Detection in Graphs. Phys. Rep. 2010, 486 (3–5), 75–174. https://doi.org/10.1016/J.PHYSREP.2009.11.002. (76) Howard, P. N.; Woolley, S.; Calo, R. Algorithms, Bots, and Political Communication in the US 2016 Election: The Challenge of Automated Political Communication for Election Law and Administration. J. Inf. Technol. Polit. 2018, 15 (2), 81–93. https://doi.org/10.1080/19331681.2018.1448735. (77) Theocharis, Y.; Jungherr, A. Computational Social Science and the Study of Political Communication. Polit. Commun. 2021, 38 (1–2), 1–22. https://doi.org/10.1080/10584609.2020.1833121. (78) Girvan, M.; Newman, M. E. J. Community Structure in Social and Biological Networks. Proc. Natl. Acad. Sci. U. S. A. 2002, 99 (12), 7821–7826. https://doi.org/10.1073/pnas.122653799. (79) Watts, D. J.; Strogatz, S. H. Collective Dynamics of ’small-World9 Networks. Nature 1998, 393 (6684), 440–442. https://doi.org/10.1038/30918. (80) Walter, N.; Salovich, N. A. Unchecked vs. Uncheckable: How Opinion-Based Claims Can Impede Corrections of Misinformation. Mass Commun. Soc. 2021, 15205436.2020.1864406. https://doi.org/10.1080/15205436.2020.1864406. (81) Mozilla Foundation. INSIDE THE SHADOWY WORLD OF DISINFORMATION FOR HIRE IN KENYA; 2021. (82) Culliford, E. Facebook cracks down on German anti-COVID restrictions group over “social harm” https://www.reuters.com/technology/facebook-shuts-down-network-linked-germananti-covid-group-launches-rules-social-2021-09-16/ (accessed Oct 10, 2021). (83) Angus, D.; Bruns, A.; Hurcombe, E.; Harrington, S.; Glazunova, S.; Montaña-Niño, S. X.; Obeid, A.; Coulibaly, S.; Copland, S.; Graham, T.; Wright, S.; Dehghan, E. ‘Fake News’ and Other Problematic Information: Studying Dissemination and Discourse Patterns. AoIR Selected Papers of Internet Research. 2021. https://doi.org/10.5210/spir.v2021i0.12089 (84) Dehghan, E.; Glazunova, S.. ‘Fake news’ discourses. Journal of Language and Politics. 2021. 20(5), 741–760. https://doi.org/10.1075/jlp.21032.deh (85) de-Lima-Santos, M.-F.; Ceron, W. Coordinated Amplification, Coordinated Inauthentic Behavior, Orchestrated Campaigns? A Systematic Literature Review of Coordinated Inauthentic Content on Online Social Networks. In T. Filibeli & M. Ö. Özbek (Eds.), Mapping Lies in the Global Media Sphere (1st ed.). 2024.Taylor & Francis. (86) Porreca, A.; Scozzari, F.; Di Nicola, M. Using text mining and sentiment analysis to analyse YouTube Italian videos concerning vaccination. BMC Public Health. 2020. 20(1), 1–9. https://doi.org/10.1186/s12889-020-8342-4 (87) Wardle, C. Misunderstanding Misinformation. Issues in Science and Technology. 2023. 29(3), 38– 40. https://doi.org/10.58875/zaud1691

Disinformation Echo-Chambers on Facebook: Funding and References

This paper is available on arxiv under CC BY-SA 4.0 DEED license. Authors: (1) Mathias-Felipe de-Lima-Santos, Faculty of Humanities, University of Amsterdam, Institute of Science and Technology, Federal University of São Paulo; (2) Wilson Ceron, Institute of Science and Technology, Federal University of São Paulo. Table of Links Abstract & Introduction Data and Methods Results Discussion and Conclusions Funding and References 2. Data and Methods 2.1. Data Collection and Preparation Recognizing that isolated bots might not represent the most critical issues on the platform, we opted to focus on coordinated activities to investigate disinformation campaigns within Facebook groups. We contend that these communities inherently function as echo chambers, where users intentionally join these Facebook groups to be exposed selectively to information that aligns with their beliefs and values. Hence, these communities offer an ideal context to delve into information dissemination dynamics. To explore this avenue, our study follows a three-step approach. Initially, we identified disinformation narratives circulating on Facebook by analyzing debunked content from two prominent fact-checking agencies in Brazil: Agência Lupa and Aos Fatos. Both organizations adhere to the transparency standards set by the International Fact-Checking Network (IFCN), a coalition dedicated to upholding excellence in the fact-checking industry [69]. Our data collection spanned from January 2020 to June 2021, yielding a total of 2,860 items. We employed an algorithm to filter out debunks that did not include the term “vaccine” or related variations in their titles. This process yielded 250 debunks specifically addressing COVID-19 vaccines. Subsequently, we subjected these debunks to qualitative analysis, confirming that they were all false or misleading, and eliminating any that did not meet this criterion. Moving on to our second step, we extracted relevant data to locate these debunked posts within Facebook. We utilized academic access to CrowdTangle, an insights tool owned and operated by Meta since 2016. It is important to note that prior research has highlighted certain limitations of this tool, such as incomplete metrics and restricted access to fully public spaces on the broader Facebook or Instagram platforms. CrowdTangle only encompasses public groups with a certain user threshold, as opposed to the entire spectrum of groups [9,70,71]. In our search, we aimed to pinpoint sentences that could be readily identified and would not yield unrelated results. For instance, we refrained from using phrases such as "COVID-19 vaccines" or similar constructs that could encompass both disinformation and credible information. Our search criteria aligned with the timeframe of the debunks, spanning from January 2020 to June 2021. Through this process, we retrieved a total of 21,614 posts containing disinformation across 3,912 groups. Importantly, this data extraction was performed after Facebook’s public announcement that it had removed false content from its platform [72]. This announcement holds particular significance, as these posts should have been eradicated from the platform by that time, which could have hindered our study. Nevertheless, our findings reveal that this announcement was not fully realized, as many debunked posts persisted on the platform. This discrepancy suggests that the volume of such posts within Facebook public groups could be even more substantial. In our third phase, we proceeded to download all the identified posts. Due to data extraction limitations within the tool, we segmented the process into timeframes, later amalgamating the data into a unified dataset. This database underwent a process of duplicate removal based on post IDs, resulting in the elimination of 1,707 duplicated entries from our initial dataset. Consequently, our final dataset encompassed 19,457 distinct entries. 2.2. Data Analysis and Visualization In prior investigations of coordinated inauthentic behavior, researchers utilized estimated time thresholds to identify items shared in near-simultaneity over a short period. Similarly, a statistical metric was proposed to identify concurrent link sharing by assessing the interarrival time – the interval difference in seconds between successive shares of URLs [28]. However, we chose not to adopt these thresholds in our study for several reasons. Unlike previous studies that centered on URLs [9,28], our analysis seeks to identify CIB within textual and visual content. Moreover, our study focuses solely on coordinated acticities among nonhuman accounts, necessitating a more stringent approach. This threshold determination was guided by similar studies that calculated this value based on a subset of the 10% of URLs with the shortest time intervals between the first and second shares [9,28,54–56]. Our empirical tests demonstrated that the timeframe calculated from the shortest intervals of 10% of URLs could range from 30 seconds to a minute. Consequently, depending on the dataset in use, this threshold might extend to around one minute, a timeframe that could feasibly be performed by humans. Given these constraints, we undertook manual testing to ascertain a timeframe unlikely for consecutive human posting. Our tests indicated that this interval should be less than 30 seconds. We acknowledge that factors like internet speed and computing power might impact this performance. Nevertheless, we opted to adopt a threshold of 30 seconds between two posts, as it represented the minimum time required for consecutive posting. Our approach also considered a recursive 30-second timeframe, accounting for the possibility of repeated new posts within short intervals – a scenario unlikely to occur frequently. This approach allowed us to identify coordinated posts that were disseminated over an extended period. Considering these temporal criteria, our computational model assessed four elements to determine coordination between posts. First, the method analyzed the “message” field, encompassing the textual content of a Facebook post. Second, it scrutinized the “description” field, which provides textual information accompanying external URLs or images shared on Facebook thumbnails. For example, the description for the post in Figure 1 was “Uma catastrófica análise sobre as vacinas contra o vírus chinês: ‘Interferem diretamente no material genético’,” identical to the content in the thumbnail. Third, our methodology leveraged CrowdTangle’s computer vision algorithm to detect text within images and ascertain if these visual contents were disseminated through automated means. It is worth noting that prior research has highlighted that CrowdTangle’s computer vision capabilities for text recognition have been a recent development and are not without limitations 71. Lastly, our process examined whether multiple entities rapidly and consistently shared the same URL, which serves as another indicator of coordinated activity [9,28]. To visualize the coordinated behaviors among different Facebook groups more effectively, we constructed a graph =( , ), where each vertex V={ 1, 2, 3,…, n} represents a Facebook group, and the edges ={ 1, 2, 3,…,em} indicate the sharing of posts with signals of coordinated activity across these groups. This process was applied to the entire dataset, resulting in the creation of Figure 2. To implement this graph, we utilized the network analysis software Gephi[73], which allowed us to visually demonstrate the stronger connections between certain groups and the presence of structures that resemble “echo chambers.” The Louvain method was employed to identify network communities within this graph [74]. This community detection algorithm relies on modularity optimization, resulting in a fast process to generate clusters [75]. Through this technique, we could pinpoint closely linked Facebook groups that formed more significant echo chambers. G V E v v v v E e e e Furthermore, we generated a second graph (see Figure 3) illustrating the five most shared instances of disinformation content. This graph, denoted as =( ), consisted of nodes of different types, where the set of disinformation content D={ 1, 2, 3,…,dn} was connected to the set of Facebook groups F={ 1, 2, 3,…, n} through an edge set ={ 1, 2, 3,…,em}, signifying the coordinated activity signals within the dataset. This graph vividly demonstrates the robust correlation between echo chambers and the widespread dissemination of disinformation. In the subsequent section, we delve into our findings and present these visualizations. G D, F d d d f f f f E e e e

Disinformation Echo-Chambers on Facebook: Data and Methods

Hi everyone! Job search can be very tedious - hundreds or even thousands of responses, waiting for a reply, constant calls, testing, and so on and so forth. I've created an Open Source, completely free and not collecting or storing any of your data browser extension that can simplify this process a bit and save almost 9 hours of your life. P.S. Here and below I will only talk about job search via LinkedIn, and the extension is designed to work in conjunction with LinkedIn (at least for now). This article is focused on finding jobs for people in Tech-industry, but the general principles apply to any specialty. Process To avoid losing a critical apply, to remind yourself, or just to have an idea of where you've applied and what conditions you've claimed for it makes sense to not just apply to jobs that interest you, but to save the "fact of applying" somewhere. Then, in the future, when you get an answer from a recruiter, you will not have to remember "What kind of company is this? Am I sure I wrote to you?". That's why the first reason to keep facts of applies is to know where you responded to. What can be a applying fact? The simplest thing is at least a link to the vacancy and the date of submission. The second reason is salary range. Not every job listing mentions it, but a lot of companies really push you to name your price. If you quote a number that's higher than what they're willing to pay, they'll just pass on you. But if you come in under their top dollar, then you're golden! You have just become a potential employee of a company that is underpaid. From this point we come to the following conclusion - it would be good to keep not only the apply fact, but also the salary range, so that when talking to a recruiter, if you are forced to "reveal your numbers" - you can rely on the data you have. The third key point is what's known as the "sales funnel" - it's all about monitoring the flow from initial applications, to first-round calls, technical interviews, and finally, job offers. At each stage, there's a filtering process. For instance, from a thousand applications, you might only land 50 first calls, 30 of those could lead to technical interviews, and maybe just 5 result in actual job offers (and those numbers aren't too shabby). Every job seeker has their unique funnel, influenced by a variety of factors like experience, tech skills, location, and even a bit of luck. But, by tracking your stats, you can make sharper predictions about your job search success. You could, for example, conduct A/B testing with different resume versions, targeting various roles or sectors. Say you're a FullStack developer with a foot in both Frontend and Backend doors. It makes sense to tailor separate funnels for each area, highlight different skills on your resumes accordingly, and after gathering a few hundred responses in each domain, you'll get a clear picture of the effort required to land your ideal role. Data If we take stock of the previous discussion, we arrive at the following checklist of information, each item's absence potentially detracting from your job search success: Company Name Knowing which company the recruiter represents when you receive a response is crucial. Assuming you haven't bombarded the same company with a slew of applications, it should be straightforward to track down your application and advance through the "funnel." Hence, this detail is absolutely essential. Link to Company Page While not strictly necessary, having a link to the company's website is incredibly beneficial for interview prep and to get a better sense of the company and its offerings. Plus, if you're interested in the company but don't get an offer, this link serves as a handy starting point for exploring new openings in the future. Role Title Surprisingly, this detail tends to slip one's mind about 30 minutes after applying. Yet, it might hold more significance and value than any other piece of information. The title can suggest the level of the position (e.g., "Senior," "Middle," "Staff") or specific areas of expertise, like "iOS Embedded Engineer." Most importantly, it helps you evaluate your interest level in the role. Considering that applying can take anywhere from 30 seconds to 10 minutes, and subsequent stages much longer, it's worth considering whether it's worth investing hours into pursuing a position that may not align with your interests among other opportunities. Job Link Keeping a link to the job posting is helpful for monitoring when a position is "closed." If you're really into a role but haven't received a response, checking the link might reveal that the company has already filled the position, prompting you to look elsewhere. Also, it's wise to review the job description before interviews to refresh your understanding of the role's requirements and other pertinent details. Salary Range Although not a deal-breaker, and not all listings include it, overlooking provided salary ranges would be unwise. This information aids in ensuring you don't undersell yourself, comparing similar roles, and understanding the overall market landscape and how your specialization fits within it. Response Date A seemingly mundane yet vitally important piece of information. It gives you a sense of the typical wait time for a recruiter's response and indicates when it might be appropriate to send a follow-up message if you're keen on getting a response but haven't received one yet. In total, we've identified 7 key data fields that describe a job vacancy. Let's now figure out how much time it would take to manually input this information versus using an extension. Time As a practical test, I decided to gather the mentioned data for 10 job postings, employing two different methods: firstly, using the classic, manual "five-finger" technique, and secondly, with the help of an automation tool. Let's dive in! Manual Method: Watch on YouTube Automated Method: Watch on YouTube What were the results? In the manual scenario, where I meticulously copy all the information by hand, prone to forgetting or misplacing data (this was my third attempt to perform all tasks error-free, like putting data in the correct column), it took 6 minutes or 360 seconds for 10 job entries. Various sources suggest that to secure a job effectively, one should aim to send out at least 1000 applications (considering this as a reasonable baseline). For such a volume, manually logging key job details would consume 600 minutes or 10 hours. Conversely, in the automated scenario, all data is copied with a single keyboard shortcut, reducing the time to gather the same amount of information to just 49 seconds. The difference is stark: the automated method is 7.35 times quicker (interestingly, this factor almost exactly matches the number of data fields intended to be saved). This means you could save approximately 8 hours and 40 minutes when processing 1,000 applications. Naturally, you might be quicker in "manual mode" than I was, which also means you'd likely be faster using automation. Alternatively, you might decide not to collect all the discussed data, which could lead to missing out on certain benefits (e.g., salary range, neglecting to research the role thoroughly, or spending extra time later searching for job/company details). The takeaway? The conclusions are yours to make. What's next? At present, the extension doesn't gather information about recruiters, as this feature seems to be exclusive to Premium users. However, once I secure a job, I plan to enhance the extension by including this capability, aiming to streamline the process of crafting follow-up messages. Additionally, here are some useful links: GitHub Chrome Web Store LinkedIn Google Sheets Template This project is entirely open-source and relatively straightforward. Currently, the extension lacks a user interface or any customization options (simply because I don't require them at the moment). If you're interested in contributing improvements, feel free to submit your pull requests. I'd welcome your contributions and update accordingly. Should you find the extension helpful, I'd deeply appreciate a star for the repository on GitHub. Moreover, a review on the Chrome Web Store could potentially lead to someone adopting a small and very cute kitten from a shelter. P.S. I've intentionally avoided comparing this simple, free extension to any market-available combiners or companion systems that serve a similar purpose. My experience with such systems has found them to be either superfluous or lacking in certain aspects. Typically, these systems offer comparable base functionality to JobSnap for free, with more advanced features locked behind a (often expensive) subscription. While third-party extensions may be slower than a quick key press-and-paste action, they also prevent you from conducting funnel experiments, as described earlier in the article. Plus, with third-party services, you relinquish control over your data. Nonetheless, automation is key, and I advocate for automating wherever possible to save time. P.P.S. If you have suggestions for improving the extension or adding support for additional sites (Indeed is next on my list), please share your ideas in the comments or reach out to me on LinkedIn.

JobSnap - How to Save 9hrs of Your Life While Searching For a Job in Tech

JobSnap - প্রযুক্তিতে চাকরি খোঁজার সময় কীভাবে আপনার জীবনের 9 ঘন্টা বাঁচাতে হয়

JobSnap – So sparen Sie 9 Stunden Ihres Lebens bei der Suche nach einem Job in der Technik

JobSnap: cómo ahorrar 9 horas de su vida mientras busca trabajo en tecnología

JobSnap - Comment économiser 9 heures de votre vie en recherchant un emploi dans le secteur technologique

जॉबस्नैप - टेक में नौकरी खोजते समय अपने जीवन के 9 घंटे कैसे बचाएं

JobSnap - テクノロジー業界の仕事を探している間に人生の 9 時間を節約する方法

JobSnap - 기술 분야 일자리를 찾는 동안 인생의 9시간을 절약하는 방법

JobSnap - Como salvar 9 horas de sua vida enquanto procura emprego em tecnologia

JobSnap — как сэкономить 9 часов своей жизни при поиске работы в сфере технологий

JobSnap - Teknoloji Alanında İş Ararken Hayatınızın 9 Saatini Nasıl Kurtarırsınız?

JobSnap - Cách tiết kiệm 9 giờ cuộc đời khi tìm kiếm việc làm trong lĩnh vực công nghệ

JobSnap - 如何在寻找科技工作时节省 9 个小时

Resume (or CV) is probably one of the most important documents you can have. It's the passport when you want to find your dream job, and a properly written resume is your visa. In two words: resume is your work and skills history summary. Your resume has only one purpose: to help an employer find out whether you're a good fit or not for a role. It has its own structure and style, so the more you follow the rules, the more are your chances to be invited to interview. In this article, I'm going to provide you an on how to write a based on more than 20 resumes I've made for different fields. This guide will suit well for IT-related specialties, but also works to non IT-related roles. ultimate step-by-step guide professional resume We will go through three steps: 1 - research, 2 - all data composition, and 3 - formatting. In the first step we will research the job market to have better keywords in our resume, in the second step we will fill our data into one document which at the last step will be formatted into the pretty form you'd like. Want to check out what is a result we're gaining to? Scroll to the end of the article: I've placed my own resume there. If you like it - this post is for you! Step 1 - Research The first and best tool you need to create a resume is Google Sheets. Yes, Excel/Sheets are your very first tools for resume creation, not Google Docs nor Word. You would ask "why?", and the answer is simple: every good work starts from research. Foremost, we need to create a spreadsheet document with three columns: , and a separate column : Required skill Frequency Vacancy URL You can copy the template from here Also, we will have to use job board websites, like or . There probably can be some other websites which are used in your region, so it's better to do some research on it and find out what suits your situation the most. LinkedIn Indeed Now we're ready to start. Use at least two-three job boards, apply filters regarding your desired position/location/experience. It's better to go as specific on position names as possible. "Software Engineer" can give you many types of software engineering, so you will have to scan numerous totally different vacancies, which is not good for research and its results. If you don't have any work experience, and there are less than 30 vacancies for non-experienced, set 1–2 years in filters to have more vacancies for research. Also, companies are ready to review your resume in some cases and help you on the onboarding stage depending on skills you have: like good knowledge of some language, knowledge of some fields like physics, marketing, food cooking etc. After setting all the required filters, we go one-by-one and scan vacancies for requirements. Fill them into your document, or increase the number if you have already seen this requirement. Save vacancy links, it will be very handy in the future. We must go through as many vacancies as we can (or the top 30-40 in total) from different sources. You can go with a more significant number, but it will not make a big difference if you have a specific position name like "React.js Front-End Developer". Your document will look like this: You will have way more skills in the document, it's just an example If there are very frequent skills, but you are not sure if you have them, it would be very useful to spend some time on testing these skills or gaining additional education to fit the required level. For example: if Spanish is a common requirement, but your Spanish is only "¡Hola!", you will have an advantage if you increase your knowledge at least to an average level like A2 or B1. So now the research step is finished, we're ready for the next step. Step 2 - Fill all the data When the research is finished, it's time to fill the data and use suitable tools for resume creation: Google Docs or Word (or any popular text redactor). Create a blank document or use this . This document will accumulate all the experiences and skills you have. template ACTUAL Add these sections to the document: - required Headline - required Contact information - required Work experience - required, but can be merged with skills block Languages - required Education - if you have them Certifications and licenses - if you have scientific publications; for bloggers, you can skip it and place URL to your blog in the contact block Publications - if you have them Awards - optional Volunteer work - required Summary - required Skills Fill the document one by one following this guide because . This order lets you achieve the correct structure of information and focus on the most important parts. THE ORDER MATTERS This also contains a couple of examples to make it easier to fill. template Headline This section is easy to fill. It's just your full name (like in your documents) and desired position name which could be found in vacancy headlines, for ex: "Manual QA". Contact information Second easy to fill section. The most important thing here is relevancy. All contact data should be relevant and actual, so the recruiter should be able to contact you with this data. Your phone number, email and work location are important to specify. For remote workers, you can also specify the location or time-zone of remote work, for example "Remote/Germany". Work experience The most important section of every resume is the work experience section. All other sections could be skipped by recruiter easily if your experience is relevant and outstanding. Here you should list in all your relevant workplaces, positions, time period and your . Don't forget that results matter more than responsibilities, they make the difference between developers who fix features and implement bugs. All results should be short, precise and include numbers. It can be started from one of the resume , for example: reverse chronological order results and achievements buzzword Redesigned the whole database structure, which improved writing and reading speed by four Also, use bullet points instead of solid text to divide multiple results in the experience section, and highlight keywords and numbers in bold to attract attention. Bullet points increase readability drastically. Just compare: Redesigned the whole database schema, which improved writing and reading speed by four. Migrated from GRPC to GraphQL when we reached GRPC data volume limits, which helped to bypass the limit and improved fetching speed from a minute to 2 seconds for 5MB payload. Developed a client-side proxy library which reduced about 7 redundant Nest.js microservices and bypass third-party rate-limits and: Redesigned the whole database structure, which improved writing and reading speed by four Migrated from to when we reached data volume limits, which helped to bypass the limit and improved fetching speed GRPC GraphQL GRPC from a minute to 2 seconds for 5MB payload Developed a client-side proxy library which and bypass third-party rate-limits reduced about 7 redundant Nest.js microservices If you don't have at least three , you can include your key responsibilities, but don't forget that measurable results are way preferable. Also, you can add one bullet point to write a small description of the workplace or project where you have worked. measurable results Languages This is a required section. However, you can skip it just by moving your languages to the skills section like this: But if you have enough space for it in your resume, you can just list all your languages with knowledge level at least on A2, in case they're relevant for your job application. Education In the education section you just list all the places where you have studied, its names, locations and time periods. If you have a high degree in one field, then just include the highest and don't include your elementary or middle school. If you have passed specialized courses, you can also include them. You also can specify one bullet on your most interesting achievement: like top place in Olympiad, scientific publication, high GPA score, etc. Certifications and licenses / Publications / Awards These three sections are optional, but if you have awards, certifications, scientific publications, they will highlight you from a dozen other resumes. The format is pretty obvious: bullet points with certification/award/publication names and dates. Volunteer work The format of this section is almost the same as work experience's format, but this section is optional most of the time. However, if volunteer work is valued for your position or field, then you have to fill it too. Summary The objective of a resume summary is to accentuate elements related to the position you are seeking, which are not detailed elsewhere in your resume. This includes showcasing transferable skills, high-level accomplishments or a context that makes your accomplishments stand out. Also, you can specify your motivation and what you're looking for. Skills The Skills section is a keyword section. It's used for resume search and matching. The better keywords you have, the higher are your chances to appear in the search results. To build a correct list of skills, you will need all the frequent required skills from , and you can add skills from your already described work experience, education and other sections. Add only relevant skills and the like "Team player" or "Result-driven". Step 1 - Research skip all cliché skills Step 2.1 - Spellcheck Use some spellcheck tools like or to fix all possible typos. . If your resume has typos, it will decrease your chances drastically. Grammarly LanguageTool It's an IMPORTANT step And we've finished the second step. Now we have all the necessary data in one document. And it's time for formatting! Step 3 - Formatting The main goal of the formatting step is to format all the most important data in one page in a readable style with (ATS) compatibility. You can try two pages if you have a lot of relevant work experience, but one page is always preferable. If you can remove some optional sections or shorten them to fit everything in one page, it's better to do so. Application Tracking System File format The resume should look the same both in and formats. PDF is more common. However, sometimes ATS could require format, so having them both is an ultimate move. .docx .pdf .docx Template The right template is important for a professional resume. So there are three main requirements for a resume template: readability, style and ATS-compatibility. The readability requirement is challenging to estimate until you fill all the necessary data, but if you pick an ATS-compatible template, it's going to be human-readable in most cases with all the relevant data. The style requirement is determined by your seniority and the work field. If you work in design, you can showcase some "bells and whistles" in your resume, but in most other cases a minimalistic style will work better. You can use templates from these lists: resume worded jobscan In the next article I will share you some more advices about resume styling, so be sure to follow my dev.to blog Template filling Now we have our resume template selected and data prepared from the previous step. The template can be filled with your data and converted to your personal resume. You can rearrange sections, but most of the time they're in traditional order. And we're done. We have our professional resume prepared to be used in your job application. Extra Step 4 - Application It's time for the extra step: remember that your resume was built using vacancy descriptions? Use the links you saved in and apply for these vacancies. You will have a pretty high chance of passing the resume filter and being invited to the interview, which will help you to test your skills and boost yourself. Step 1 My resume Here is my resume! I built it by using my own guide and following steps I've described: you can find it on and make your own copy. Here Google Docs For those who didn't know, I've started my own ! More than that, I regularly help people in from scratch or using existing ones. So check out my for more information and content! private consultations creating good resumes Telegram channel

Writing a Professional Resume: the Ultimate Guide

The last ten years have been significant here at . We started our journey in December 2013 as a small team of developers on an outsourced project for a marketing company, a partner of Emaar Properties. The project was a request from one of the co-founders, now CTO and Solution Architect, who had just completed the implementation of indoor navigation kiosks for shopping malls. WebLab Technology Remote-first At the beginning of the project, we rented an office room in a business center located in an industrial zone in one of the cities in Ukraine. After 6 months of work, we received additional funding from the client and needed more people to join the team. It so happened that some of our team members were due to leave at the end of that year: one of the key engineers was moving to France, and the other was returning to Dubai. It was quite difficult to hire engineers with the right skill set, mainly because we were losing out to large companies in terms of office quality and space management. But this is what led us to develop our . At the time, in 2014, it was our big competitive advantage because there was a significant pool of engineers who wanted to work remotely. remote-first hiring strategy After this initial growth period, we realized that technical competence alone was no longer enough to make a hard-hitting team. Our remote-first approach necessitated engineers who could work autonomously were able to make decisions on their own and were ready to take responsibility for the result. Dedicated Teams We realized that working in the format of dedicated teams is the best approach for . It means we can establish teams to work exclusively on projects for a particular company while also expanding its internal staff. This model has a number of important other advantages: WebLab Technology 1. A dedicated team focuses only on the needs of a specific client and is always available to respond quickly to solve their business problems. More than just being available, dedicated teams always show up and deliver for their clients, providing reliable, consistent execution. Full focus on client goals. 2. Our team fully adapts to the client’s corporate culture, following established rituals such as daily stand-ups, weekly planning, or progress-tracking meetings. We immerse ourselves in the company’s business objectives and choose the methods of cooperation that are most appropriate for them. Organic integration with the business. 3. — cloud technologies, front-end development, DevOps, etc. We help our clients find exactly the right specialists for their projects. Ready (quick) access to expert knowledge in various fields 4. . Young companies may not have the right culture or approaches, and methodologies to work with engineering teams. We know lots of ready-to-use techniques like proper Scrum, cultural patterns, engagement activities, etc. Ready to use patterns for performance 5. . The client pays only for the necessary functions, not for the maintenance of an additional office, equipment, hiring/recruitment, training, insurance, accounting, legal, taxes, etc. In addition, the team can be flexibly scaled up as needs change. Cost-effectiveness Eastern Europe offers a vast human resource pool that global companies can tap into. Moreover, Eastern European workers have very high and in-demand skill sets — sometimes higher than in Western countries — combined with comparatively lower wages. For example, the average salary of a Senior Software Engineer in is $58k, in — $60k, in — $64k. In the , this figure reaches $145k per year for exactly the same skills and experience. Ukraine Poland Estonia US Therefore, working with from Eastern Europe is an opportunity to get high returns and professional, motivated engineers at optimal prices — a mutually beneficial relationship for all parties. Senior Dedicated Development Teams Values that unite our team Here at WebLab Technology, we have a strict set of values that inform every decision we make. But we did not form them in one day. Our values are a long evolutionary process that is still ongoing. Values let our teammates, clients, and partners know what to expect from us because when people share common values, it creates trust and predictability in relationships. 1. : Always eager to learn and adapt. Open-mindedness Embracing a modest self-assessment. Humility: 3. Upholding consideration and empathy for others. Respect: 4. Striving for excellence autonomously. Self-driven: 5. Addressing issues with sincerity and courage. Honesty: 6. Treating each project as our own, ensuring its success. Ownership: Cooperation with Shaman as one of our turning points Our dedicated development teams usually work in two formats: they extend the client’s existing teams but have a specific area of responsibility, or they are fully responsible for the entire R&D direction of the client company, as was the case with . Shaman is one of our main clients that we are very proud to work with. The company’s technical component is fully implemented by WebLab. It is now an established business with customers among the world’s leading pharmaceutical corporations, such as , , , . Shaman Novartis AstraZeneca Takeda Galderma Our collaboration with started back in 2015 with the idea of an iOS app for internal use to create smart canvas presentations. These presentations needed to be easy to adapt to the audience, sharable, and simple to design. The app has generated a lot of market traction, and it is now used by global enterprises around the world. It was on the basis of this application that we created a B2E SaaS company, which now employs more than 30 of our engineers. Shaman Currently, Shaman is actively promoting its flagship product, , in the pharmaceutical market. In line with Shaman’s mission, the company seeks to empower Life Science Organizations’ content teams with the best no-code platform available, enabling them to create tailored content for healthcare professionals (HCP) in the most efficient way possible. ShamanGo The recent shift of leading pharmaceutical corporations towards digital strategies has increased the demand for unique content. However, many of these companies do not have time to quickly create and manage huge amounts of information. This is where ShamanGo comes in — its users can generate high-quality omnichannel content in minutes by integrating with the leading platform . Thanks to close cooperation with , ShamanGo has become the optimal solution for accelerating content production in the context of the digital transformation of the pharmaceutical industry. Veeva Veeva Systems Over our years of cooperation with Shaman, we have achieved certain successes that have shaped our work together. Some of our proudest achievements include: ● Scaled the team to 30+ engineers; ● Implemented Scrum and Scrum of Scrums to maintain consistency and motivation across our seven dedicated teams; ● Developed a strategy for advanced quality control (a vital concept in the B2E sector due to its demand for stability) and ; 99.9%+ uptime ● Obtained certification; SOC2 Type 2 ● Created a global infrastructure in the US, Europe, and Asia Pacific ● Achieved a high level of infrastructure automation and quality control; ● Achieved top scores on the Framework methodology; AWS Well-Architected ● Supported the Certification process; Veeva Technical Partnership ● Launched a data-driven decision-making system; ● Implemented integration with various third-party platforms, including Salesforce; AI-strategy We believe that and so it is one of our main goals to stay ahead of the competition in this domain. AI will change the world We started early work with AI in 2019, focusing on routing problems, multiple-objective genetic algorithms, and letters using computer vision. Today, we have more than ten successful AI cases in our portfolio. We moved into more active integration of generative AI technologies into business processes in 2022. This has led us to focus on the development of AI agents and RAG solutions based on models such as GPT-4, Llma2, Stable Diffusion, etc. As in other industries, we can see the benefit AI could bring to software engineering and plan to embrace this change. Our past projects include AI solutions for optimizing workflows in pharmaceutical companies. For example, we developed Magic Copy for , as an AI agent based on GPT-4 that generates optimized email templates following simple input instructions from a user. Shaman Another successful case is the use of computer vision in the FoodTech database, which we designed for OllyFood. For this project, we implemented an automated quality control system for dishes and products based on image analysis. The computer vision-based system analyzes images of dishes, identifies all ingredients, assigns quality scores, and detects up to 80% of deviations before the product reaches the customer. We continue to actively develop AI solutions for various industries. Our goal is not only to keep up with technological progress but also to set trends and shape the future of AI. Optimizing Engineer Teams with Data Lake Metrics: A Strategic Approach Building effective teams that succeed is a difficult task in both sports and business. You may have watched the movie Moneyball, which shows how a baseball team manager started using analytical techniques to select players based on statistics rather than subjective impressions of scouts. This allowed him to build a competitive team with a limited budget. In the IT business and software development teams, similar logic applies. We at WebLab Technology build a team and evaluate performance based on data and metrics, as this kind of information is a cornerstone of our industry. One of the key approaches for us is measurement and automation at all levels: the company as a whole, teams, and staff roles. For example, we have an that tracks the number of completed story points, planned scope of work, standard Scrum reports, the share of unplanned tasks and bugs, business value points, pull request sizes, code integration frequency, QA returned count, etc. automated management system In addition to hard metrics, we also quantitatively analyze : motivation, team atmosphere, and the realization of one’s capabilities. However, career advancement in the company mostly depends on the results of hard metrics. soft metrics Remote working gives us full digitalization and the ability to continuously track all processes in the company — from the work of engineers to customer satisfaction. We make our personnel and strategic decisions based on all this collected data and analytics we have at our disposal. We believe that the best results are achieved by combining technological and human factors. Hiring slowly, hiring right: Why do we prioritize a thorough candidate search? When it comes to hiring new employees at , we avoid rushing things, even if it may delay the start of their work. In our opinion, accelerated recruitment creates significant risks in the long run, which almost always outweigh the potential short-term benefits. That’s why our hiring cycle is almost than the market average, and we pay a lot of attention to assessing the technical skills of potential senior developers. WebLab Technology three times longer The standard search for potential candidates consists of 6 stages: WebLab Technology . We thoroughly review resumes and invite those who initially meet our requirements and have relevant skills. Deep profile screening . Sometimes it’s called a homework assignment. Candidates undergo a specialized Selection Task that evaluates abilities for the specific role. Selection challenge or project The focus is on understanding how the candidate handled specific challenges or tasks in the past, aiming to predict their future performance. Behavioral interview. . Candidates showcase hands-on skills through coding challenges and sample projects. Coding interviews The candidate is typically asked to solve real-world coding problems, demonstrate their coding abilities, and showcase their understanding of relevant technologies within the industry. Domain/coding interview with leading engineer. Our CTO assesses the candidate’s understanding of system design principles, their ability to make informed decisions, and their proficiency in creating scalable and efficient solutions. System design interview with CTO. For ten years, we have honed our ability to recognize the optimal combination of technical skills and the right human qualities, which allows us to expand our dedicated teams with truly motivated and professional engineers. We are also open to hiring new specialists, especially AI Prompting Engineers. If you are an area specialist and think you are a match in terms of values and philosophy, we invite you to check out the vacancies on our website: https://www.weblab.technology/jobs Technology and logic We mainly work with B2B SaaS solutions that require solving specific business problems at scale and primarily focus on logic, functionality, and metrics rather than aesthetic visualization. We have worked with startups at different stages — in their earliest days and when they were in an active growth phase, building up their capacity and staff. Due to our flexibility, we adapt to the needs of our clients at any stage, regardless of the size of the startup and business model. In addition to startups, has implemented complex solutions that require optimization and scaling for global enterprise companies. WebLab Technology Today, our main technical focus is on AWS, logic-intensive micro frontends, microservices, and AI. We also prepare our clients to pass standard certifications and audits and maintain a high level of quality in the areas of security and compliance. For example, we helped our client obtain the . ShamanGo SOC 2 Type II certification Ten years To celebrate the 10th anniversary of our company, we decided not to organize pompous offline events but instead to transfer our celebration budget of more than 10 thousand USD to the Foundation and support those who are now defending Ukraine and the rest of the civilized world. Kolo “The Kolo Foundation is doing a great job. We’ve been cooperating with the foundation for a while now, and I think it’s the best use of our team’s celebration budget,” says WebLab Technology CTO and Solution Architect . Oleksandr Knyga In 10 years, has grown ten-fold. Today, our team consists of professional engineers working on products of varying complexity, and the company has in its portfolio such clients as , , , , . WebLab Technology ShamanGo AstraZeneca Novartis Bryj (ex. FollowAnalytics) Emaar Properties We constantly develop specialists within dedicated teams and share expertise between them for a synergistic effect. Unlike classical outsourcing companies, we are primarily a team of strong engineers, where even the CEO is ready to commit to the repository. Our development focuses on an increase in the average level of seniority of engineers rather than quantitative growth.

Celebrating 10 years of WebLab Technology: Our Story of Growing Through Dedicated Teams

ওয়েবল্যাব প্রযুক্তির 10 বছর উদযাপন: আমাদের ডেডিকেটেড টিমের মাধ্যমে বেড়ে ওঠার গল্প

Wir feiern 10 Jahre WebLab-Technologie: Unsere Geschichte des Wachstums durch engagierte Teams

Celebrando 10 años de tecnología WebLab: nuestra historia de crecimiento a través de equipos dedicados

Célébration des 10 ans de la technologie WebLab : notre histoire de croissance grâce à des équipes dédiées

वेबलैब टेक्नोलॉजी के 10 साल पूरे होने का जश्न: समर्पित टीमों के माध्यम से आगे बढ़ने की हमारी कहानी

WebLab テクノロジーの 10 周年を祝う: 専任チームによる成長のストーリー

WebLab 기술 10주년 기념: 전담 팀을 통한 성장 이야기

Comemorando 10 anos de tecnologia WebLab: nossa história de crescimento por meio de equipes dedicadas

Празднование 10-летия технологии WebLab: наша история роста благодаря преданным командам

WebLab Teknolojisinin 10. yılını kutluyoruz: Özel Ekiplerle Büyüme Hikayemiz

Kỷ niệm 10 năm Công nghệ WebLab: Câu chuyện phát triển của chúng tôi thông qua các nhóm tận tâm

庆祝 WebLab 技术 10 周年：我们通过专业团队成长的故事

Dissecting Video Games and If They Are Art: A Non-Gamer's Analysis

ভিডিও গেম ব্যবচ্ছেদ করা এবং সেগুলি যদি শিল্প হয়: একটি নন-গেমারের বিশ্লেষণ

Videospiele analysieren und ob sie Kunst sind: Die Analyse eines Nicht-Spielers

Diseccionando los videojuegos y si son arte: un análisis de un no jugador

Disséquer les jeux vidéo et s'ils sont de l'art : une analyse d'un non-joueur

विच्छेदित वीडियो गेम और यदि वे कला हैं: एक गैर-गेमर का विश्लेषण

ビデオ ゲームを解剖し、それがアートであるかどうか: 非ゲーマーによる分析

비디오 게임을 분석하고 그것이 예술이라면: 비게이머의 분석

Dissecando videogames e se eles são arte: uma análise de quem não é jogador

Анализ видеоигр и являются ли они искусством: анализ негеймера

Video Oyunlarını İncelemek ve Sanat Olup Olmadıklarını: Oyuncu Olmayan Bir Analiz

Phân tích trò chơi điện tử và liệu chúng có phải là nghệ thuật: Phân tích của một người không phải là game thủ

剖析视频游戏以及它们是否是艺术：非游戏玩家的分析

Let's face it, job hunting is a job on its own and this writer has had a fair share. In Web3, I noticed conversations about what a “Web3 resume” should look like. It is typically different from what an HR would term as a good CV worthy enough to pass the first screening stage through ATS for an interview. It's a simple, one-page document designed with maybe Canva and contains major roles with less attention to “wins” in each role. For instance, if you decide to announce a vacancy for a role in , maybe for a community manager or discord moderator on X (still called Twitter), and also ask respondents to drop their CV in the comment, you will find something like this: Web3 Or you may just rather get links to portfolios, which I think is even much better because it provides an opportunity for the candidates to showcase their past work and still hint to the recruiter that they have the solution to fit in that role. Because formal job hunting with resumes is quite annoying, let me let you in on how I ‘discarded’ mine to get a senior role as Head of Marketing and Content at an on-chain gaming company. My story from the top Ten months, 1000+ applications, and a brutal 99% rejection rate later, I was ready to throw in the towel. But then, I discovered that I could beat ATS to get interviewed. So, I had to start customizing my resume for each job. I blocked at least 2-3 hours daily to apply for about five jobs, carefully inserting the necessary keywords and rewriting my resume as well as . Now, that's a dedicated punishment because I was on it every single day, including weekends. cover letters So imagine that one day I'm to apply for all these roles and I don't have an existing customized CV: Head of Marketing Marketing Manager PR and Communications Manager Marketing Lead Content Marketing Manager That means I have to carefully customize each resume before answering all the other questions and then clicking “apply.” In customizing my resume, I carefully had to edit out previous job experiences that were not relevant to the specific job I was applying for. As someone whose last full-time job experience was in a B2B SAAS company, it meant I had to garner enough Web3 experience to include in my resume. I already had prior experience working in 2 Web3 companies, but they weren’t recent. Most times, HRs carefully look at your recent job experiences to check if they align with the role you applied for. Having that in mind, I became more detailed in customizing each resume per job. Really, this cycle is the absolute ghetto, especially when you still get ditched after a series of interviews. One life hack, though : “ The more interviews you attend, the more confident you become and the higher your chances of getting a job soon”. How I Got the Head of Marketing Role To be frank, possibilities become realities when opportunities meet preparation. I was more than prepared. I learned how to ace interviews after attending 40+ interviews. I binge-watched videos on YouTube, especially on how to ask your interviewer questions so you can have some level of control during the conversation and leave a lasting impression. For questions specific to my career, I had become way used to hearing them constantly being asked during my interviews that I could answer them correctly without thinking twice. I finally became a boss so much that I became picky with job offers that came my way. My quest for more led me to LinkedIn. While I had attained a high level of preparation, I intensified my job search. I used various keywords to search for posts regarding job vacancies on LinkedIn, and that was how I came across the Head of Marketing role. I was doing that before now, but I wasn't so lucky in getting the role of my choice. The post led me to apply directly on , but I checked the location and saw that my location was about 7 hours behind their time, and I felt applying directly via Linkedin might be a reason for me to be disqualified. LinkedIn I went through the job description again and noticed an email address included. I sent an email directly, attaching a link to my portfolio made with read.cv. Additionally, I attached a Google document showcasing further evidence of my work with other Web3 projects, highlighting major freelance projects in particular. Thankfully, within 48 hours, I was invited for an interview. The interview Like any other interview I showed up for, I took it upon myself to learn about the company and find out things they were doing wrongly for me to adjust if granted the opportunity, so this was no different. I joined the Google Meet link, and I was interviewed by four people, including one of the co-founders and CEO. For every question asked, I had prompt, intelligent responses to deliver. Not just that, I had answers that I could tie to the Web3 space to prove to them that I can as well duplicate such in the role. When it was time for me to ask questions, I didn't fail to. I asked them what challenges they were facing and what were their expectations of me to fit into the role, they did answer and promised to get back to me. True to their word, the next day brought a job offer. The entire process unfolded faster than I'd ever seen - no tasks, my shared documents were enough proof, and no CV was needed. My tactical responses, intertwined with the Web3 space, were exactly what my employers wanted to hear. After getting the job, I then discovered that I had won a tight competition against about five others who applied with a conventional CV.

How I Got a Job in Web3 as 'Head of Marketing' Without a CV

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