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Tensorflow Vs. Keras: Comparison by building a model for image classification

A complete guide to text processing using Twitter data and R. Why Text Processing using R? With the increasing importance of computational text analysis in research , many researchers face the challenge of learning how to use advanced software that enables this text analysis. Currently, one of the most popular environments for computational methods and the emerging field of “data science” is the R statistical software. However, for researchers that are not well-versed in programming, learning how to use R can be a challenge, and performing text analysis in particular can seem daunting. In this step by step guide one can learn that performing text analysis in R is not as hard as some might fear. This is an introduction into the use of common techniques, with the aim of helping researchers get acquainted with computational text analysis in general, as well as getting a start at performing advanced text analysis studies in R. Why R? R was specifically designed for statistical analysis, which makes it highly suitable for data science applications. Although the learning curve for programming with R can be steep, especially for people without prior programming experience, the tools now available for carrying out text analysis in R make it easy to perform powerful, cutting-edge text analytics using only a few simple commands. One of the keys to R’s explosive growth has been its densely populated collection of extension software libraries, known in R terminology as packages, supplied and maintained by R’s extensive user community. Each package extends the functionality of the base R language and core packages, and in addition to functions and data must include documentation and examples, often in the form of vignettes demonstrating the use of the package. The best-known package repository, the Comprehensive R Archive Network (CRAN), currently has over 10,000 packages that are published. Text analysis in particular has become well established in R. There is a vast collection of dedicated text processing and text analysis packages, from low-level string operations to advanced text modeling techniques such as fitting Latent Dirichlet Allocation models, R provides it all. One of the main advantages of performing text analysis in R is that it is often possible, and relatively easy, to switch between different packages or to combine them. Recent efforts among the R text analysis developers’ community are designed to promote this interoperability to maximize flexibility and choice among users.4 As a result, learning the basics for text analysis in R provides access to a wide range of advanced text analysis features. Why Twitter Data? Twitter is an online microblogging tool that disseminates more than 400 million messages per day, including vast amounts of information about almost all industries from entertainment to sports, health to business etc. One of the best things about Twitter — indeed, perhaps its greatest appeal — is in its accessibility. It’s easy to use both for sharing information and for collecting it. Twitter provides unprecedented access to our lawmakers and to our celebrities, as well as to news as it’s happening. Twitter represents an important data source for the business models of huge companies as well. All the above characteristics make twitter a best place to collect real time and latest data to analyse and do any sought of research for real life situations. If you need other datasets, you can download pre-exiting datasets of various use cases like cancer detection to Q&A dataset to sports comments to chatbots. Here is various text classification datasets. Or if you have your unique use case, you can create your very own dataset for it. You can download images from the web and to make a big dataset in no time, use an annotation tool like , where you upload the raw data and tag manually in a ziffy. Dataturks Dataset: In order to extract data of Twitter we need to create a Twitter Application. STEPS TO CREATE A TWITTER APPLICATION 1.Navigate to My Applications. ( ) Link 2. Since I already have this app created, it appears on my page. Click on “create New App”. Fill in all the details of the application. 3. Once all the details are filled in and verified you will be granted the customer and access keys. INSTALL AND LOAD R PACKAGES: R comes with a standard set of packages. A number of other packages are and installation. For the purpose of this post, we will need the following packages: available for download ROAuth: Provides an interface to the OAuth 1.0 specification, allowing users to authenticate via OAuth to the server of their choice. Twitter: Provides an interface to the Twitter web API. Let’s start by installing and loading all the required packages. install.packages( )
install.packages( ) ( , lib.loc= ) ( , lib.loc= ) ( , lib.loc= ) ( , lib.loc= ) ( , lib.loc= ) ( , lib.loc= ) ( ) ( , lib.loc= ) ( ) ( ) "twitteR" "ROAuth" library "NLP" "~/R/win-library/3.3" library "twitteR" "~/R/win-library/3.3" library "syuzhet" "~/R/win-library/3.3" library "tm" "~/R/win-library/3.3" library "SnowballC" "~/R/win-library/3.3" library "stringi" "~/R/win-library/3.3" library "topicmodels" library "syuzhet" "~/R/win-library/3.3" library "twitteR" library "ROAuth" Connect your twitter account to R, in order to extract the required tweets. consumer_key <- consumer_secret <- access_token <- access_secret <- setup_twitter_oauth(consumer_key, consumer_secret, access_token, access_secret) 'YOUR CONSUMER KEY' 'YOUR CONSUMER SECRET KEY' 'YOUR ACCESS TOKEN' 'YOUR ACCESS SECRET TOKEN' Extracting tweets using a particular hashtag: tweets_g <- searchTwitter( , n= ,lang = )
tweets_a <- searchTwitter( , n= ,lang = )
tweets_f <- searchTwitter( , n= ,lang = )
tweets_tech <- searchTwitter( , n= ,lang = ) "#google" 1000 "en" "#amazon" 1000 "en" "#facebook" 1000 "en" "#technology" 1000 "en" Convert this extracted data to a dataframe which makes it more readable and easier to work with. amazon_tweets <- twListToDF(tweets_a)
google_tweets <- twListToDF(tweets_g)
facebook_tweets <- twListToDF(tweets_f)
tech_tweets <- twListToDF(tweets_tech)

View(amazon_tweets)
View(google_tweets)
View(facebook_tweets)
View(tech_tweets) Here is how the data would look like: It is very clear that in the text section of the data, which is what we need to process there are a lot of special characters and unnecessary data which we would not require. Hence it becomes extremely important to pre-process this data and then we can continue with out analysis. Below is a code to pre-process the data and remove tabs, blank spaces, links etc. This section can be modified according to one’s requirements. google_text<- google_tweets$text
amazon_text<- amazon_tweets$text
facebook_text<- facebook_tweets$text
tech_text<- tech_tweets$text google_text<- tolower(google_text)
amazon_text<- tolower(amazon_text)
facebook_text<- tolower(facebook_text)
tech_text<- tolower(tech_text) google_text <- gsub( , , google_text)
amazon_text <- gsub( , , amazon_text)
facebook_text <- gsub( , , facebook_text)
tech_text <- gsub( , , tech_text) google_text <- gsub( , , google_text)
amazon_text <- gsub( , , amazon_text)
facebook_text <- gsub( , , facebook_text)
tech_text <- gsub( , , tech_text) google_text <- gsub( , , google_text)
amazon_text <- gsub( , , amazon_text)
facebook_text <- gsub( , , facebook_text)
tech_text <- gsub( , , tech_text) google_text <- gsub( , , google_text)
amazon_text <- gsub( , , amazon_text)
facebook_text <- gsub( , , facebook_text)
tech_text <- gsub( , , tech_text) google_text <- gsub( , , google_text)
amazon_text <- gsub( , , amazon_text)
facebook_text <- gsub( , , facebook_text)
tech_text <- gsub( , , tech_text) google_text <- gsub( , , google_text)
amazon_text <- gsub( , , amazon_text)
facebook_text <- gsub( , , facebook_text)
tech_text <- gsub( , , tech_text) google_text <- gsub( , , google_text)
amazon_text <- gsub( , , amazon_text)
facebook_text <- gsub( , , facebook_text)
tech_text <- gsub( , , tech_text) #convert all text to lower case # Replace blank space (“rt”) "rt" "" "rt" "" "rt" "" "rt" "" # Replace @UserName "@\\w+" "" "@\\w+" "" "@\\w+" "" "@\\w+" "" # Remove punctuation "[[:punct:]]" "" "[[:punct:]]" "" "[[:punct:]]" "" "[[:punct:]]" "" # Remove links "http\\w+" "" "http\\w+" "" "http\\w+" "" "http\\w+" "" # Remove tabs "[ |\t]{2,}" "" "[ |\t]{2,}" "" "[ |\t]{2,}" "" "[ |\t]{2,}" "" # Remove blank spaces at the beginning "^ " "" "^ " "" "^ " "" "^ " "" # Remove blank spaces at the end " $" "" " $" "" " $" "" " $" "" A little more pre-processing — Removal of stop words! What are Stop Words? When working with text mining applications, we often hear of the term “stop words” or “stop word list” or even “stop list”. Stop words are basically a set of commonly used words in any language, not just English. The reason why stop words are critical to many applications is that, if we remove the words that are very commonly used in a given language, we can focus on the important words instead. Stop words are generally thought to be a . It really can mean different things to different applications. For example, in some applications removing all stop words right from determiners (e.g. the, a, an) to prepositions (e.g. above, across, before) to some adjectives (e.g. good, nice) can be an appropriate stop word list. To some applications however, this can be detrimental. For instance, in sentiment analysis removing adjective terms such as ‘good’ and ‘nice’ as well as negations such as ‘not’ can throw algorithms off their tracks. In such cases, one can choose to use a minimal stop list consisting of just determiners or determiners with prepositions or just coordinating conjunctions depending on the needs of the application. “single set of words” google_tweets.text.corpus <- tm_map(google_tweets.text.corpus, (x)removeWords(x,stopwords()))
amazon_tweets.text.corpus <- tm_map(amazon_tweets.text.corpus, (x)removeWords(x,stopwords()))
facebook_tweets.text.corpus <- tm_map(facebook_tweets.text.corpus, (x)removeWords(x,stopwords()))
tech_tweets.text.corpus <- tm_map(tech_tweets.text.corpus, (x)removeWords(x,stopwords())) #clean up by removing stop words function function function function We are done pre-processing our data, and are ready to do some analysis. Data visualizations (like charts, graphs, infographics, and more) give analysts a valuable way to communicate important information at a glance. If you want a stunning visualization format to highlight important textual data points, using a word cloud can make dull data sizzle and immediately convey crucial information. What are Word Clouds? Word clouds (also known as text clouds or tag clouds) work in a simple way: the more a specific word appears in a source of textual data (such as a speech, blog post, or database), the bigger and bolder it appears in the word cloud. So let’s generate some word clouds and find out some of the frequent and important terms being used in the tweets we have extracted. ( ) wordcloud(google_tweets.text.corpus,min.freq = ,colors=brewer.pal( , ),random.color = ,max.words = )
wordcloud(amazon_tweets.text.corpus,min.freq = ,colors=brewer.pal( , ),random.color = ,max.words = )
wordcloud(facebook_tweets.text.corpus,min.freq = ,colors=brewer.pal( , ),random.color = ,max.words = )
wordcloud(tech_tweets.text.corpus,min.freq = ,colors=brewer.pal( , ),random.color = ,max.words = ) library "wordcloud" #generate wordcloud 10 8 "Dark2" TRUE 500 10 8 "Dark2" TRUE 500 10 8 "Dark2" TRUE 500 10 8 "Dark2" TRUE 500 Below are the word clouds for the data I have: Next I will be doing sentiment analysis on the tweets. Introduction to Sentiment Analysis What is Sentiment Analysis? Sentiment essentially relates to feelings; attitudes, emotions and opinions. Sentiment Analysis refers to the practice of applying Natural Language Processing and Text Analysis techniques to identify and extract subjective information from a piece of text. A person’s opinion or feelings are for the most part subjective and not facts. Which means to accurately analyze an individual’s opinion or mood from a piece of text can be extremely difficult. With Sentiment Analysis from a text analytics point of view, we are essentially looking to get an understanding of the attitude of a writer with respect to a topic in a piece of text and its polarity; whether it’s positive, negative or neutral. In recent years there has been a steady increase in interest from brands, companies and researchers in Sentiment Analysis and its application to business analytics. The business world today, as is the case in many data analytics streams, are looking for “business insight.” In relation to sentiment analysis, I am talking about insights into consumer behavior, what customers want, what are customers like and dislike about the products, what their buying signals are, what their decision process looks like etc because in the end of the its the customers for whose satisfaction these businesses work for. I have used the inbuilt sentiment analyzer in R, which uses the NRC sentiment dictionary to calculate the presence of eight different emotions and their corresponding valence in a text. mysentiment_google<-get_nrc_sentiment((google_text))
mysentiment_amazon<-get_nrc_sentiment((amazon_text))
mysentiment_facebook<-get_nrc_sentiment((facebook_text))
mysentiment_tech<-get_nrc_sentiment((tech_text)) Sentimentscores_google<-data.frame(colSums(mysentiment_google[,]))
Sentimentscores_amazon<-data.frame(colSums(mysentiment_amazon[,]))
Sentimentscores_facebook<-data.frame(colSums(mysentiment_facebook[,]))
Sentimentscores_tech<-data.frame(colSums(mysentiment_tech[,]))

names(Sentimentscores_google)<- Sentimentscores_google<-cbind( =rownames(Sentimentscores_google),Sentimentscores_google)
rownames(Sentimentscores_google)<- names(Sentimentscores_amazon)<- Sentimentscores_amazon<-cbind( =rownames(Sentimentscores_amazon),Sentimentscores_amazon)
rownames(Sentimentscores_amazon)<- names(Sentimentscores_facebook)<- Sentimentscores_facebook<-cbind( =rownames(Sentimentscores_facebook),Sentimentscores_facebook)
rownames(Sentimentscores_facebook)<- names(Sentimentscores_tech)<- Sentimentscores_tech<-cbind( =rownames(Sentimentscores_tech),Sentimentscores_tech)
rownames(Sentimentscores_tech)<- ggplot(data=Sentimentscores_google,aes(x=sentiment,y=Score))+geom_bar(aes(fill=sentiment),stat = )+
  theme(legend.position= )+
  xlab( )+ylab( )+ggtitle( )


ggplot(data=Sentimentscores_amazon,aes(x=sentiment,y=Score))+geom_bar(aes(fill=sentiment),stat = )+
  theme(legend.position= )+
  xlab( )+ylab( )+ggtitle( )


ggplot(data=Sentimentscores_facebook,aes(x=sentiment,y=Score))+geom_bar(aes(fill=sentiment),stat = )+
  theme(legend.position= )+
  xlab( )+ylab( )+ggtitle( )


ggplot(data=Sentimentscores_tech,aes(x=sentiment,y=Score))+geom_bar(aes(fill=sentiment),stat = )+
  theme(legend.position= )+
  xlab( )+ylab( )+ggtitle( ) #getting emotions using in-built function #calculationg total score for each sentiment "Score" "sentiment" NULL "Score" "sentiment" NULL "Score" "sentiment" NULL "Score" "sentiment" NULL #************************************************************************************* #plotting the sentiments with scores "identity" "none" "Sentiments" "scores" "Sentiments of people behind the tweets on tech giant GOOGLE" "identity" "none" "Sentiments" "scores" "Sentiments of people behind the tweets on ecomerce giant AMAZON" "identity" "none" "Sentiments" "scores" "Sentiments of people behind the tweets on Social Netwoking site FACEBOOK" "identity" "none" "Sentiments" "scores" "Sentiments of people behind the tweets on tech as a whole" From the following plot of sentiment analysis on tweets with #Google, its observable that Google has a positive impact on the consumers and is extremely trusted by them. There have lately been quite a good number of anticipations maybe on their products or the company employee’s or any other possibility. From the following plot of sentiment analysis on tweets with #Amazon, its observable that the E-Commerce giant, has maximum tweets being positive and similar to google has won the trust of consumers. Apart from these there is a notable amount of joy among their customers. The tweets with #Facebook show a little different trend. Lately, there seems to be a lot of negative sentiment associated with the tweets on facebook. But along with that there is also a trust which the company has maintained. In general, the tweets on technology have a lot of positivity and trust among the people, across the globe. These are only a few very obvious sentiments which I have described. You can always look at the visualizations and draw multiple conclusions about the data. Conclusion Text Processing and Sentiment analysis emerges as a challenging field with lots of obstacles as it involves natural language processing. It has a wide variety of applications that could benefit from its results, such as news analytics, marketing, question answering, readers do. Getting important insights from opinions expressed on the internet especially from social media blogs is vital for many companies and institutions, whether it is in terms of product feedback, public mood, or investors opinions. Sentiment analysis is a difficult technology to get right. However, when you do, the benefits are great. Look for a tool that has uses Natural Language Processing technology and ideally with machine learning capabilities. Look for a vendor that treats sentiment analysis seriously and shows advancements and updates in their sentiment analysis technology. Complete code.

Text Processing and Sentiment Analysis of Twitter Data

Paper sales proposal is rapidly becoming an old fashioned thing in a connected and interactive world. It's clear that sales proposal have evolved in many ways. Sales proposal files have been replaced by fancy proposal tools. You can also call it a technological leap. Today's selling world has become more competitive than ever before. Buyers have become more sophisticated. Now, the look and feel of your sales proposal is equally important as the content and quality of it. In this day and age, you can't have a general sales proposal approach; they have to be cutting edge to dazzle your potential clients. It doesn't have to be a crazy formal document, especially if you don't need to present it to the bank or the investor. The time has come where you need to create a glamorous living sales proposal that will shine and help you win the deal. In simple words "Interactive Sales Proposal". Why You Need To Implement An Interactive Sales Proposal? To make the entire reader experience memorable. How often you view a PDF file on mobile or on a tablet? Quite often, right? But do you go through the same struggle as me? Like, Wait for the PDF file to download.Zoom in to read the content.Swipe left to right to read.Again zoom out. Now, imagine the same file goes to your prospective client in the form of a sales proposal. Clearly, you missed your chance. As they say, First impression is the last. I have some more reasons to tell you why PDFs are outdated? They Are Not Interactive A typical monotonous proposal doesn't influence the client to read furthermore. When a proposal contains only plain text and a few images the prospective clients will not be able to focus on the main objective. Imagine you have the latest video of your product that explains everything about it and you want to include that in your proposal but because you are using PDF you can't. We live in a world where turning your idea into reality has made it more possible than ever before. And this lack of interactivity of PDFs gives full stop to all your amazing ideas and again decreases your chances of winning the deal. They Are Not Trackable Has this ever happened to you? You sent an important mail and expect a quick reply. But, after time passes.....nothing. You start wondering whether the recipients ever opened your email? But fortunately, there are some tools that allow you to track your email. But imagine, you will be notified whenever someone views your proposal, or you could know time that person spends on reading it or which part of your sales proposal holds his attention the most, etc. Wouldn't that be great? But unfortunately, you won't be able to implement all these things that give you all the insights if you send proposals in PDF. They Are Not Flexible According to , 64.4% of email opens occurred on mobile devices. Adestra Viewing PDFs on mobiles still remains a terrible experience. And the main reason is that PDFs are not flexible at all. Mobile screen readers are not able to pick up the text successfully. It's really frustrating to pinch the screen, again and again, to zoom out and zoom in to find your spot in the document. It's visually impossible for your prospective client to read PDF proposals on mobile, it will make it harder to communicate the value of your product and sadly you will have to face one more rejection even if your product or service fulfills the pain points of the prospective client. Lastly, It Was Absolutely Nice Knowing You PDF PDF has lived its life amazingly. Without a doubt, PDF was once a pacesetter in online paperwork. However, it has started showing it's age. Because the information that is locked inside a document won't sustain in a rapidly increasing mobile world. Businesses are exploring new ways to manage their data. How To Create Interactive Sales Proposals? Wouldn't it be amazing if your prospect notices every bit of your sales proposal without a single distraction? Let's find out how. Use Video To Make Your Sales Proposal Effective The face of a sales proposal has changed. But many companies still serve their information via text and then again keep wondering about the low conversion rate. Statistics are clear, humans are visual creatures. Video is the way people prefer to learn anything new. It's exactly similar to Visume (Video resume). We all know that video resumes are extremely interactive. Each minute in your Visume is worth a thousand words. You can convey a lot in a 3-minute Visume than what you could have with a 200-page booklet about yourself. So, why not simply copy the same idea and create an awesome mp4 sales proposal. It is an excellent way to stand out from the competition. Audiofy Your Sales Proposal Imagine, your prospect loves early morning jog and while jogging if he listens to some interesting stuff on podcast that immediately lifts up his mood. So, don't you want to grab that opportunity? Audio interactivity provides another level of engagement. You can highlight your key strengths and convince the prospect that you are the right person for a project. And plus it shows, that you are ready to go the extra mile. Include Interactive Pricing Table You can create your proposal as a Webpage. In that, you can add interactive pricing tables with a range of pricing options where customers can edit the quantities, select products or services that best fit their needs. In short, they can create a tailored version of your product or service for them. Interactive pricing table also allows clients to select additional services. For example, if you have some additional services like content strategy development plan, social media marketing etc, and if they want one of those services, then your proposal should display the updated pricing in real-time. Your proposal should have an ability to communicate pricing with your prospect. GIF It Up It is been a while now when the globe was introduced by GIFs. The more the technology gets older the more easily it fades away. But there are few exceptions like GIF. At the age of 31, they are becoming more popular and fashionable than ever. GIFs can attract anyone's attention and make your average elevator pitch distinct from others. It gives you easiest way to connect with your prospect, show off your key elements in style, and make the process joyful. Brad Zeff, Chief Content Officer and General Counsel of Giphy and Samantha Scharff, the CEO of are two people that are trying to animate the globe and redefine digital communication. We’re the people that bring you all the GIFs. Giphy Studios "Our mission is to make everything move" says Zeff. So you can make use of these GIF’s to make an otherwise plain text proposal into an exciting moving picture. Wind-up: An interactive sales proposal is a new approach to convey one very important message that the sales proposal don't have to be that boring, formal document. It's time to break the routine and create something exciting. We created the for readers that want to improve their sales processes. sales proposal checklist

Why Interactive Sales Proposal Is the Next Big Thing?

For a full list of DID protocols see here (feel free to add any if I missed them) In light of the recent Cambridge Analytica scandal, important questions have been raised on personal data processing and the case against large conglomerates such as self-regulating. Witnessing Mark Zuckerberg’s recent court testimony, it was interesting to see the benefits that come with self-regulation: that of non-liability, which comes in handy when business’s need a quick get-out-of-jail-free card. But let’s examine a more pressing issue that was repeatedly investigated by the Senate and Zuckerberg, that of data security and the impending matter of data governance. facebook As Senator Jon Tester, of Montana, told Zuckerberg… “You’re making about forty billion bucks a year, and I’m not making any money — it feels as if you own the data,” Of course, it is Facebook’s prerogative to request data from their users to enable them to sell ads and to power their business. However, when users provide consent to facebook for using their data, it is generally expected that their personal data is protected and not fall into the hands of shady 3rd parties that violate personal data to swing elections.So what can be done to regulate data privacy and tackle the problem of data governance? **Give power back to the people.**One step in the right direction is the EU’s GDPR initiative ( ) that expand personal data rights for EU residents. 25.05.18 Get to know your rights! By now most businesses or entities that deal with EU consumer data are on their way to full GDPR compliance. To get a more comprehensive understanding of your rights as a data subject you can view the official GDPR document here . Before diving into decentralised identities I would like to add that the founding principles of GDPR are a much needed and welcoming solution to some of the problems individuals experience with personal data processing. They ultimately give consumers further power to regulate the data they provide to centralised entities and 3rd parties… But herein lies the problem — If you want to use platforms or apps ” that monetise through ads, you don’t have a choice to hand over your data as a substituted payment. Furthermore, most of us are unaware of the amount of data that we are providing centralised service’s like Google, Facebook or Linkedin for using their services— Just conduct a data request on Facebook to see how many GB’s of unnecessary data they have stored on you, no doubt you’ll be surprised.The familiar phrase— could alternatively interpreted But if our data is governed and monetised by external authorities, should we not have the power to do the same? I mean it is data. “for free but unnecessary “if you are not paying for it, you are the product” “If you are not paying for it, your data is”. our The Next Step. Luckily for us, recent developments in distributed ledgers offer disruptive solutions that are set to change the way we, as individuals, control and govern our data.Let me explain how. The official GDPR document I mentioned above uses the term ‘ ’ to refer to a body or entity that handles and processes our data for legal or profitable purposes.**But what if the data subject (individual) could equally act as the data controller…..?**Well, for a start, we would have ultimate control and ownership of our own information. We decide what data of ours gets processed and by whom.Furthermore, can from it… Already, we are witnessing initiatives such as , , and who are paving the way to building shared data economies built on incentive protocols that allow individuals to monetise from their own data (just like Facebook does with our data). Sure, it means heightened responsibility, but that’s what self-governance is - .Imagine a world where we don’t to rely on centralised authorities to manage our personal data or access our sensitive information to validate us.Through truly owning our data, we can choose who has access to it online and allow centralised authorities to access only the data needed to use their services. Two questions to consider: data controller we profit Datawallet Madana Sovrin personal responsibility have necessary Will large data-powered business’s such as Google/Facebook even need to conform with ‘individual governance of data’ given that we currently rely so heavily on their services? —Probably not. In the case of GPDPR, they are required to comply with EU law, so perhaps lobbying for a personal data protocol could be the answer. 1) legislated How could individual data governance even work? 2) Enter Decentralised (self-sovereign) Identities - DID’s Due to the immutability of cryptographically “sealed” ledgers and the architecture that DID’s provide, we are able to enhance our ability to govern our personal data in a much more secure and way than before.For instance: Current digital identities, such as passports, rely mainly on a centralised process that involves a personal claim (individual assertion) backed up by a proof (a valid document) which is then validated by an external authority who stores, or has a copy of your personal data on centralised servers. Every time we submit our data we are habitually storing our sensitive information across multiple centralised databases, making it difficult to track and update not to mention vulnerable to violation. portable Decentralised identities aim to achieve individual global uniqueness without the need for a central registration authority. Christopher Allen helps to summarise this well: “The user must be central to the administration of identity. That requires not just the interoperability of a user’s identity across multiple locations, with the user’s consent, but also true user control of that digital identity, creating user autonomy.” What partly provides this autonomy is allowing the individual to essentially create and request ‘claims’ to their identity and other data such as driving licences or reputation on distributed ledgers that are cryptographically verifiable by the external party they are communicating with. By using ‘verifiable claims’ we never actually need to share our personal data with anyone in the first place. I will examine this in more depth below but first, let us get a better understanding of the DID objectives as specified below by the W3C design goals. (built on Christopher Allens ) decentralised identifier A life with Alacrity Integral components of DID’s and what they aim to achieve. It’s important to note that the concept of decentralised identities are a product of over 13 years development. Only now, thanks to a multitude of technological advancements, refined principles, decentralised protocols and the hard work of the W3C community, are we beginning to see real world DID applications come into existence. (see for a list) here Effect of GDPR. Before we explore the architecture of DID’s it is important to quickly investigate the effects GDPR has on distributed ledgers.Irritatingly, since the EU commission began devising GDPR legislation early on in 2009, of technology was still in its infancy and not considered as a solution to the issues facing data privacy. As a result, it has bought a few contradictory issues regarding GDPR and on-chain data storage to fruition.The main issue is the GDPR’s ‘right to be forgotten’ act (erasure of data). Due to the immutability of data stored on-chain, it is impossible to erase data that has been written to a block. As Andries van Humbeeck excellently concludes in his article: world application blockchain The Blockchain GDPR paradox: “Since throwing away your encryption keys is not the same as ‘erasure of data’, GDPR prohibits us from storing personal data on a blockchain level. Thereby losing the ability to enhance control of your own personal data.” Humbeeck goes on to argue that blockchain is a more secure and accessible system for personal data storage compared to centralised servers. However, quantum computers have already began posing a threat to the standard key encryption protocols we currently use and is predicted by some to be rendered obsolete in the next ten years.Interestingly, the also takes GDPR into consideration in section 5.4: W3C DID specification “Although a core feature of distributed ledgers is immutability, the DID method specification MUST specify how a client can revoke a DID record on the target system, including all cryptographic operations necessary to establish proof of revocation.” ) ( : revocation may now actually be possible using note CL proofs So how do DID’s get round this ‘right to be erased’ conundrum? The simple answer: Don’t store your data on-chain, store a ‘claim’ instead.. Enter Self-Sovereign architecture. A few companies such as (built by Evernym) are already using protocols that provide on-chain ‘verifiable claims’ (proof) which validate the individuals data to the questioning authority without revealing the data.It does this by storing an on-chain encrypted verified claim (individual assertion) in the form of a hash which also acts as a public key to cryptographically validate the users data. To help clarify, below are a few of the fundamentals that make self-sovereignty work. Sovrin actual Source: Image provided by Soverin’s white-paper 1: — A questioning authority can use an issuers/merchants key to validate if your is true using a mathematical proof equation that the data provided is indeed valid without the need to reveal the actual data to anyone. Zero knowledge proofs (ZK proofs) claim 2. — They allow users to safely decrypt messages between each other using a set of mathematically relatable numbers/hashes. Multiple key consensus is used and stored with service providers to prevent loss or theft of a key. Public and Private keys 3. They are the on-chain ‘vessel’ for public keys and prove governance of the individual by storing the timestamp and digital signatures needed to prove a ledger. DID Descriptor Objects (DDO’s) — A simple use case could be: If I needed to set up an account to purchase an online product, which is currently very common, I would need to provide bank account details…information that the company could use to market further products too. However, If I showed my DID they would only need to verify the claim to assure that the information was true, not my banking data. So it seems that we have a robust solution that takes into consideration GDPR while also utilising the security and accessibility of a blockchain to offer an interoperable identity that can be issued to external parties to validate without compromising the users data. A matter of consent. At the moment, anybody can still request data from anyone as long as consent is given.The matter of individual consent and trust between parties has, until now, been contested in the past through written documentation, signatures and legislation.In comparison, the above protocols use the truth of mathematics to successfully bypass the issue of consent in a polluted data economy. Trust is put into the reliable hands of mathematics. Further documents referenced and thanks from:w3C community group — — The ICO points out a recommended code of conduct for data sharing https://w3c-ccg.github.io/did-spec/#dfn-did https://ico.org.uk/media/for-organisations/documents/1068/data_sharing_code_of_practice.pdf With thanks to Kedar Deshpande and Julio Santos. Zeff is a community and marketing expert at Fractal Blockchain: We believe in raising the status of crypto-communities by advocating self-governance and freedom of choice through transparency and trust. Join our forward-thinking community to receive live updates on our partner projects, latest blockchain developments and exclusive token launches that solve real-world problems. www.trustfractal.com

How decentralised identity protocols (DID’s) will revolutionise consent.

On-chain Privacy with Decentralized Computation?

As a developer, how many times each day do you look something up online? I'm not talking about a simple piece of syntax, I'm talking about the things that are a bit harder to find. For example: Is there a good way to compile C to WebAssembly and run it in a browser without needing to modify the code itself? Can the Stripe UI export promotion code redemptions as a CSV? Is there a tool for hot module reloading in Go? good Is it socially acceptable to go out in public in South Dakota with blue hair? While working as a team lead a few years ago, I remember asking Jeffy, a developer on my team: "Is there a way to get to use pointers for nullable columns instead of the sql.Null types?" sqlc Jeffy went heads down for... much longer than I would have expected. After more than a full day of research, he came back with: "No, there isn't a way. I found something that seemed promising, but it doesn't work. I think we should fork the project and add it ourselves." I've got some questions. Hol' up. First, you're telling me that you found what we want in the API of a well-known project, but it's broken and knows that it's broken but you? You are confident there aren't any skill issues involved? open-source no one else Second, you're telling me that your recommended course of action is for our team of four to fork a project with many thousands of lines of code and maintain our own version ad infinitum? All for a little quality of life improvement? No, Jeffy. No. What was Jeffy's problem? Counterintuitively, I believe Jeffy's problem was that he didn't know when to give up. I don't mean on the task as a whole, I mean on each individual path he was taking to find the answer. Here's a chart. Jeffy was too attached to his initial searching methods. Maybe he was too attached to one page from the docs, to his initial search query, or to Google as a search mechanism altogether. Jeffy found a and became stuck. He should have bailed and tried looking elsewhere. local maximum so much sooner If I don't find good evidence that the answer I'm looking for exists in the place I'm searching, I'm bailing pronto. That doesn't mean I'm 100% certain it doesn't exist, but you usually don't have to read an entire Stack Overflow thread to know whether or not it relates to your problem. I'm honestly amazed at how some developers take so long to look stuff up. Now, in their defense, even if you're an efficient searcher, you can still get stuck in a "quagmire": a local maximum. If you're not careful, you can find yourself reading on and on about a topic that seems like what you're looking for, only for it to skim over the details that you actually need. Bummer. exactly I'm a big fan of using AI as a replacement for some of my would-be Google searches, but Chat GPT is the quagmire, i.e its the ultimate local maximum. It's the worst kind of quagmire because at every step it will confidently reassure you that it does, in fact, know the answer. When you insist that it's wrong, it confidently continues to provide information that sounds correct but isn't. ultimate If you use Chat GPT for programming assistance, you to develop a strong sense of when ChatGPT is making stuff up. In short, need you need to know when to bail. RTFM Sometimes we talk about "Googling things" as a skill unto itself, and it kind of is. But similar to ChatGPT, it's less about formulating the most pristine search query, and it's more about knowing when to give up on a goose chase. Does the SERP indicate that your original search query was a good one? No? Bail. Does the first page you visit have a directly relevant title or first paragraph? No? Bail. After spending another minute on the page are you still convinced the answer is somewhere below? No? Bail. Is it likely the answer can be found more easily in the docs, the user manual, or, , the code itself? Yes? Bail. gasp Reading the manual, perusing the official docs, or digging through the source code usually takes longer than skimming an on-topic article or tutorial, but SEO-spammed articles often coalesce into an entire sea of local maxima. They tease you by scratching the surface of what you're looking for, but if your issue isn't the most common one, you can waste hours trudging through the garbage. Sometimes, taking the into the topic is the fastest (only?) way to find answers to the more esoteric questions. time to go deep Back to Jeffy I don't want to leave you hanging on this story. As it turned out, the documentation for SQLC was complete, but it was tricky to understand how to use pointers for nullable columns if you landed on the wrong page. There are a lot of configuration options for SQLC, and it's easy to get lost. I just cloned the repo, grepped for "pointer", and found the code that parsed the configuration option. It was clear after just a few minutes of reading the source that we just needed to do three things: Specify the we want (e.g. "string" instead of ) go_type sql.NullString Set nullable: true Set pointer: true Here's the code: overrides:
  - db_type: "text"
    nullable: true
    go_type:
      type: "string"
      pointer: true Sometimes you gotta rtfm. Sometimes you gotta suck it up and grep the code. Also published here. By the way , is awesome and if you like Go you should be aware of it. sqlc

Every Developer Should Learn to Give Up Sooner

The idea of building a community has always been a romantic one in the business world. What if your revolutionary startup concept could bring together a group of like-minded and passionate people? It’s easy to see which companies have successfully drawn a crowd with their innovative ways — think of Apple’s avid devotees, or the many thousands of Peloton junkies. But the best communities don’t always form after the fact. Some of the most successful businesses today set out to build a community right from the get-go; their entire business model is based not around commodity, but community. HubSpot, for example, wouldn’t be where it is today without its community-first growth model. I recently sat down with Lloyed Lobo on my podcast. He’s the co-chair of , a community of over 100k+ founders and tech professionals. Our conversation made me realize that building a community can be just as important to success as the product itself — so that’s what we’re talking about today. Traction Commodity vs. Community: What’s the Difference? The traditional business model is a pretty straightforward one: your business sells a product or service, and then you charge customers for it. This is a commodity-based model on the idea of providing value through an object or experience. But there’s a new model on the scene, and it’s being used to incredible success by the likes of HubSpot, Harley-Davidson, Salesforce, and more. The operates on a different principle: providing value through relationships. community-based business model It’s not about selling products or services — it’s about connecting people with shared interests to create meaningful experiences that go beyond what could be achieved individually. This is the basis of any good social network, but in this case, those connections are made for economic and social purposes. Great Examples of Community-Based Businesses So how does the community-based business model actually work? I browsed around to see which companies are doing it right, and found some pretty incredible examples. H.O.G. Local Chapters One of the most obvious is . When the company booted up almost 120 years ago, it was your classic commodity-based business. But as a fanbase began to grow, a culture formed — and the brand became infamous, as we know. Even people with absolutely zero interest in motorcycles know what a Harley is these days. Harley-Davidson Harley-Davidson’s community is called ‘H.O.G. Local Chapters’, and the letters stand for . The word ‘HOG’ was being thrown around way back in the roaring ’20s when Harley owners dominated racing events. Now, though, the brand has made it an official part of its identity — and being a H.O.G. member has plenty of perks. Harley Owners Group For just $49 per year, Harley owners get access to things like exclusive magazines, roadside assistance, event access tickets, Visa points, merch, and a whole list of other benefits. Family members can even join for a slightly lower fee. Most importantly, members join their local Chapter; they can rally and ride alongside other passionate Harley owners. I’m not a motorcycle fanatic, but even as I was looking through the H.O.G. website, I could feel the energy of the community — and that’s exactly what makes it so powerful for Harley-Davidson as a business. They’re profiting off of the joy and camaraderie shared between fellow riders. And they certainly treat their members well! LEGO Ideas Toys are toys — and like it or not, they cycle through phases. No one plays with Polly Pocket anymore. LEGO has found a way to make itself immortal, though, which I have great respect for. The LEGO business strategy has always struck me as one of the very best. In a nutshell, LEGO has built a community around collection and nostalgia. You can join the and post your designs for everyone else to see — and if your designs are particularly great (meaning you get lots of votes from the community), your design might make it onto LEGO shelves. LEGO Ideas community Looking through the LEGO Ideas profiles, it was clear that most of the community grew up playing with LEGO and are relishing the opportunity to use their old skills on new tricks. Just look at these bios from some of its community members: “I love lego and have since I was a child and I got my first lego set. I have been hooked ever since. Now I share the joy of lego with my daughter and my nieces and nephews. I love to spread the joy of lego. I think it’s the most amazing toy or even just the best product in the world. It changes lives for the better.” — Vonbrikenstein “Since 2014 I have been gripped by Lego fever again. With the Ideas set “Ghostbusters Ecto-1” (21108) I found my way back to the small bricks.” — Hob72 “I’m a lifelong fan of LEGO who has been lucky enough to translate a childhood passion for design into a fulfilling career as an Architect. My LEGO passion was re-ignited when playing with my children and now includes collecting, construction in real life, and digital LEGO design (primarily in Stud.io).” — Jeffy-O “Rediscovered the joy of being creative with Lego and being completely absorbed into the building process.” — Leg0flow Heartwarming stuff, right? But I bet you’re wondering how this all gets monetized. To be blunt, most of the LEGO profits come from their toy sales. However, there’s a definite business strategy to all of this. Here’s how it works: Within the LEGO Ideas community, new competitions and challenges are run pretty much every week. The company posts exercises to help its members level up their brick skills.Members can sign up for free and post their designs. They can also support other creators by voting. For the particularly talented builders, their designs go in the running to be made into real-life LEGO sets (like this awesome typewriter you might have seen floating around the internet!) So, how does it all make money? Well, with thousands of members and avid builders… they’re going to need a of LEGO. The community keeps people buying more bricks to fuel their creative passions. It’s perfect, really. lot Traction Since Lloyed Lobo is the inspiration for today’s newsletter, it’s only right that I mention , of which he’s the co-chair. Traction If you haven’t heard of Boast.ai before, it’s an innovative software that helps companies get the most out of R&D tax credits minus the usual rigmarole. Traction is its community of over 110,000 members — tech heads, business owners, investors, and innovators. The whole community is based around this idea of innovation in entrepreneurship. With industry icons like Jeff Lawson of Twilio, Kip Bodnar of HubSpot, and Julia Hartz of Eventbrite, it’s bursting with the most inventive and hardworking minds. Conferences, podcasts, and webinars deliver high-caliber education to thousands upon thousands of members each year. One of their most recent webinars was run by Vinay Hiremath, co-founder of Loom — so they’ve got some impressive names contributing to the community. It’s a simple monetization process; I imagine there’s a fee to attend conferences and webinars, which provides funds for the company and value to the community members. The members themselves seem to absolutely love the experience: “Traction is THE community to supercharge your business by learning from thought-leaders of the fastest-growing companies in the world!” — Daniel Saks, AppDirect Salesforce and have a very similar setup in which they bring together like-minded people to share their ideas and expertise. If you look around at some of the most successful companies today, you often don’t need to dig too far to find an adjoining community. HubSpot How To Monetize Your Community It’s pretty standard for the community model to use monetization strategies like paid events, subscriptions, and product add-ons. But really, it’s up to the individual business to find out what works best for them. Here are some of the most convincing strategies I found while researching: It’s rarely a good idea to charge a membership fee; usually customers just won’t bother, since they have no proof it’ll be worth their cash. Make the membership free, but lock certain pieces of valuable content (webinars, templates, etc.) behind a paywall. Restricted access. Slashing prices for your members is often the best way to get more sales through the community. Plus, it makes people feel special — which is invaluable when it comes to customer loyalty. Discounts, coupons, and other deals. Offer opportunities for relevant businesses to advertise or showcase their products in forums and other areas of the community. Ads and product placement. This is one strategy that can help if you’re charging membership fees. On the H.O.G. website, there’s a huge list of all the extra benefits you get with a Harley-Davidson membership. It’s certainly impressive, even to an outsider looking in. Make sure your members know what they’re getting for their money. Make your perks obvious. Have you got a product that members can, and would like to, trade among themselves? You can monetize that by adding a small fee for each transaction. Create a trading space. This works particularly well if you’ve got a figurehead within your community who people look up to. Sell tickets to exclusive webinars or even one-on-one consulting sessions with that person. Leverage exclusivity. You can get pretty creative with this. Just keep in mind that the money won’t always flow straight away; community building doesn’t happen overnight. But Is It Worth The Hassle? This is a great question because, let’s face it — community building isn’t easy. Businesses that naturally gather a crowd of engaged users are fortunate, since they can set up a monetized structure around the pre-existing group. But even then, it’s hard to give your community something of value they’ll actually pay for. That being said, the benefits of a community-based business model are enormous. You’re not just relying on a product to garner and maintain popularity; you’re benefiting from the collective energy of people who actively use and advocate for your product or services. It’s a self-sustaining system that can bring an extra layer of profits to your business. Think about LEGO Ideas, for example. They’ve got billions of dollars coming in from toy sales, LegoLand tickets, online stores, and so on. But on top of that, they’ve managed to dredge up an entirely new stream of revenue just by setting up a community for nostalgic builders. Never underestimate the power of nostalgia! And, of course, there’s the added bonus of increased customer loyalty. People who are part of a thriving and engaged community will naturally be more loyal to your brand than those who just buy a product off the shelf. We’ve all seen — customers value human connection much more than they used to. The community-based model provides that connection in spades. the statistics What Will The Future Hold? I truly believe — as does Lloyed Lobo — that future businesses are going to be increasingly more community-based. It’s impossible to look away from the success of initiatives like Traction and LEGO Ideas, and it’s only a matter of time before other companies start to adopt the model. That being said, there are some caveats. It’s important to remember that communities don’t just appear out of thin air; they have to be nurtured with care and attention. You’ve got to give your customers something special — whether that’s exclusive deals or insider knowledge — that’s worth their time. Lloyed also mentioned to me that he only recommends this model to people if they have a desire to bring people together. That’s the only way it works — if you’re passionate about your product and care enough to provide value to a community of users, then this model should work for you. Are you a business-driven innovator? Could ? I’d love to hear your thoughts on the community-based business model in the comments! community be your new currency Also Published Here

Lloyed Lobo Talks About the Community-Based Business Model

Minecraft is a sandbox computer game created by Mojang Studios. Markus "Notch" made the Java game. In Minecraft, players build and destroy blocks in three-dimensional worlds. The game modes are survival and creativity. In survival, players should find their structure, supplies, and food. They help with block-like mobs or moving creatures. Creepers and zombies are examples of the more dangerous types. In creative mode, the aim is to explore, build, and survive. Players can join many Minecraft online games (called "servers"), and some of these games involve fighting other players. They may find and concentrate on unrefined components, make devices and things, and fabricate designs, earthworks, and primary machines. Contingent upon their picked game mode, players can battle unfriendly hordes and collaborate with or go up against other players in a parallel world. In , players move around in a vast open world generated by a set of Minecraft rules in three dimensions. the skindex What is Minecraft skin? A "skin" is an image that you can apply to your character in the video game Minecraft to alter their appearance. If this is your first time playing the game, the characters Alex or Steve will be automatically assigned to you as your starting skin. Characters Alex and Steve share the role of the game's primary protagonist. Alex is a very fair-skinned man with long orange hair. She is seen here sporting a brown pair of pants, a pair of gray boots, and a light green tunic with a green belt. Steve has dark brown skin and short brown hair. His hair is also brown. He is seen here donning a t-shirt in a lighter shade of blue, blue jeans, and a pair of gray shoes. The game's downloadable content is available in the form of skin packs. Remember that the Skindex packs are not available in all game editions. You can download Minecraft skin packs on Windows 10 Edition, Nintendo Switch, Playstation, and Xbox. There are five modes, but the two most popular modes are: Creative. Survival. What is the creative mode? In Minecraft, one of the primary gameplay modes is called Creative Mode. In Minecraft's Creative mode, the Survival mode elements are disabled. It lets players build and destroy structures and mechanisms with infinite blocks and flying. It also alters background music. This is the primary game mode. The creative mode is simply easy, where you do not need to stress over getting ravenous or harmed. Since it is easy, you don’t need to disturb yourself over anything. You can fabricate monstrous designs and play in a more casual setting. You're not restricted to strolling and running, item all things considered. Flying is a choice in Creative Mode. You likewise approach each block, apparatus, weapon, elixir, book, and food thing accessible in the game. This mode is magnificent for investigating the various approaches to working in Minecraft. What is the survival mode in the Skindex? In survival mode, players interact with villagers and defend against nighttime mobs. Everything requires effort, unlike creative mode. Blocks are limited. The survival world is difficult for new players. In Survival Mode, gamers are dropped haphazardly into a world at daybreak. They have 10-20 continuous minutes to accumulate assets, create devices, and things, collect asylums and track down food to make due. At the point when haziness falls, they additionally need to fight beasts and crowds. The nature of Minecraft games: Everything in the Minecraft world is tended to by cubical blocks, for instance, trees, soil, sand, water, grass, and blooms. Blocks can be eliminated and put into your stock with the right instrument (for instance, a digging device to get soil). You can make some of these blocks into various things. Numerous players construct distinctive designs like palaces, pinnacles, and pyramids, which serve as their homes on the planet. The skindex on Minecraft has a constant cycle; after sunset, beasts come out. Everything from zombies and monster bugs to skeletons equipped with bows and bolts to the famous green "creepers" that approach you and detonate, managing harm to you and obliterating everything in their area, leaving an opening in the ground. Minecraft skins: In the game Minecraft, skin is a picture that changes what your personality resembles. Steve has short earthy colored hair and dark earthy colored skin. He wears a light blue shirt, pants, and a few dim shoes. Many custom Minecraft skins can be created and downloaded from the internet. What is the skindex? Skindex for Minecraft allows players to create custom skins using the Skin Editor and upload them to skindex. As a result, Skindex enables you to utilize a wide variety of user-created Minecraft Skins. Some might be modeled after well-known historical figures, while others would provide you with the look you're going for. Popular Minecraft Skins in the skindex Among Us: Among Us is a suspicious skin that is so great for multiplayer. You can choose this skin if you are playing with your friends. So take on the appearance of the characters from Among Us and have complete faker rounds with the universe of Minecraft. Being a fan is simply digging in for the long haul, and there could be no more excellent method for hopping in. This skin, like most others, functions admirably in the Minecraft Bedrock edition, so make it a point to them reciprocally. Goku Goku is a nostalgic cartoon character. Goku can travel on a reflective cartoon character's train. Don't miss Goku's stop on your dreamy cartoon character's train. Goku can fly creatively. He's famous for his orange jacket and impressive muscles. Skindex: Minecraft characters can have many different skins, such as a new persona, cherry blossoms, baby blue, hidden talents, etc., using the Skindex's Wardrobe function. Skindex has the most extensive collection of Minecraft skins you could consider. Batman: The Batman skin for Minecraft is among the most well-known available options. The Batman Minecraft skin is an excellent addition to the game, as it features the famous DC superhero. Bruce Wayne, a wealthy American who lives in Gotham City and uses the alias Batman, is the man behind the mask in the DC Universe. Batman is a unique superhero because he does not possess any superhuman abilities and relies solely on his immense wealth to fund the incredible technology he employs in his fight against criminals. Between 1966 and 2022, 14 Batman movies were made. Bob the builder: Bob, the builder, depicts the main character of a British children's stop-motion television series. On the wistfulness train and welcome your lifelong companion to Minecraft to remember recollections with this exceptional skin and vast long stretches of development in the game. Tommy Vercetti: With Tommy Vercetti, you will not be bored. This skin gives you the Grand Theft Auto (GTA) protagonist from Minecraft. Jeffy: Jeffy, the magnificent animated character from the SuperMarioLoagan games, is magnificent. He generally wears a yellow shirt, and in this manner, as you can see in the above picture. For what it's worth, Minecraft hasn't changed the style of the garment and has addressed the Jeffy character in the game. Block Camo: You can hide your identity in the game with the help of this block camo, which functions similarly to the creeper skin for bedrock. This time, you can turn into an environment, a prickly plant, or a tree rather than a substance. It's one of the best time trick-based skin packs you can use on your companions, so make sure you pick it up. Thanos. The adorableness of this MCU reprobate is something you will not generally anticipate. Be that as it may, this skin gets our most certainty well-known Wonder character with precision noticeable till the shade of the vast stones. A precise-looking Thanos, yet with a significant hint of charm, makes it an ideal expansion for the Wonder fans playing Minecraft. Chewbacca: This furry bear-like animal has its character. Star Wars fans have made an honest effort to catch this in numerous ways, yet the first Chewbacca skin is our number one. Although Minecraft's reality isn't as advanced as Star Wars, this skin fits quite well. Deadpool: The advantage of being a Wonder fan is that interminable astonishing characters are brought into your number one games. Take a stab at playing as Deadpool in the blood-red backwoods biome and experience limitless tasteful power. Creeper: The creeper is maybe the most notable horde in all of Minecraft. A horde nearly characterizes the actual game. You can involve this skin for no particular reason and utilize it to alarm your companions. This skin ensures that your feet and arms are undetectable for a more sensible impact. You probably won't have the option to trick the in-game hordes. However, tricking different players will unquestionably merit the work. Anime Legends II: This is a legendary skin pack for Anime fans. It features twelve (12) characters from various popular anime series, such as One Punch Man, Naruto, and Attack on Titan, among others, and original characters. Legacy Skin Pack: This is one of Minecraft's most requested and unbelievable skin packs. The pack offers an old-style Minecraft experience for totally free. The group behind the skindex for Minecraft presents it so that you can expect great starter skins from numerous past versions. Moreover, you can attempt the heritage-style Minecraft in your program for the Java people until they discharge this pack for you. Tetris: Individuals had been setting blocks together before Minecraft was created. Indeed, the exemplary block disposal game Tetris has received accolades for its exceptionally innovative skin. Its famous varieties and block style will return you to the past. Minecraft Skin for Mobile Devices You can explore, create, play, and survive with friends on various platforms.  Ascend rugged mountains, discover intricate cave systems, and excavate expansive ore veins. Explore the biomes of lush caves and caves with dripstone. Candles are a great way to light up your surroundings and show off your skills as a mountain climber or cave explorer. You can download the skindex for Minecraft on your mobile devices, like Android and iOS. Minecraft for mobile devices lets you explore new worlds and build everything from houses to castles.  To fight dangerous mobs in survival mode, you must mine deep. In contrast, there are unlimited resources in the creative mode. Does Minecraft have a free trial? You may wonder if you can get a free Minecraft trial if you want to play the entire game instead of the anniversary version. Minecraft offers several free trials. Visit Minecraft's free trial page to see your options. That page states that Android, Windows 10, PS3, PS4, and PS Vita users can download Bedrock, Minecraft's main version, for a free trial. Links to the storefronts are also on that page. How To Change Minecraft Skin With Skindex Visit https://www.minecraftskins.com/ by typing in the address. This will open the Skindex library. The most popular Minecraft skins will all be visible on the home page. "Download." Go to https://minecraft.net/. Go to Profile. The drop-down menu's first choice is this option. Click "Choose a File." Select the downloaded skin file. Click the Open button. The bottom-right portion of the window contains this option. The profile page will have your skin file uploaded. Select Upload. This will alter the character's skin for your current account. The steps for playing Minecraft custom character for free This free version is the 2009 Minecraft creative mode, released for the tenth anniversary but still playable. Visit https://classic.minecraft.net/ to play Minecraft online without downloading or installing. You'll get a link to play with up to nine friends after a level is automatically generated. After creating a username and pressing start, you can left-click to place or mine blocks, right-click to toggle between them, and move with WASD. The game's age limits it. There are no mobs, 32 blocks, and all the original bugs remain. You'll also lose all your retro recreations if you close the tab. This is a free “the skindex” game meant as an anniversary gift, not a platform for the sandbox game. Steps To Download & Install Skins For Minecraft: Download Go to https://www.minecraftskins.com/ and select any of the skins that catch your eye. After you have decided on the skin, a new page will load up, offering you several different ways to export the skin. The next step is to select "Download" from the menu on the right side of the screen and click it. Once you click the button, a PNG file will download. It will be a PNG file of low quality, and you can find it in the folder labeled Downloads on your computer. Install Launch https://www.minecraftskins.com/ on your device, and on the home screen's right side, below your character, select the "Profile" button to access your player profile. You will then take to the screen where you can select a character to apply the skin. You can choose from various characters here and click "Edit Character." Open your skin options by clicking the second tab on the left. You can import new skins by selecting the "Import" option found in this area, followed by the "Choose New Skin" option. At this stage, a window for Windows Explorer will open up on your screen. The PNG skin file you want to use is located in the Downloads folder on your computer, so navigate to that folder. The skin will load into the game once you click the "Open" button. As soon as you have finished, you will load your skin into Minecraft, and you will be able to play the game with the same skin applied to the character you control. Conclusion: The Skindex gaming stage is known for its charming and stimulating characters. The majority of players travel the world and play on their official sites. Additionally, they make their picture by picking one person from the rundown of thousands of great skins. For some, the best Minecraft skins to consider is still a mystery. It's a fun game that can teach you things and is one of the most entertaining video games available. Aside from Steve and Alex, who come with the game, you can make your characters or download them from the internet. FAQ Q: Can I use Minecraft on my mobile device? Yes, Minecraft is available for download on iOS and Android devices. Search for "Minecraft Pocket Edition" on your iOS or Android phone. After finding the game, click "Install" and let it download and install. Q: Can I report a copied skin? A flag is located below the thumbs-down button on every skin page. Click the flag icon on the offending skin page and choose "Copy skin" and submit the report. Minecraft will check within 72 hours. It will remove the copied skin. Q: How to save your favorite skins? Always add skins to your wardrobe to keep track of them. You can always change your original skin by going to your wardrobe page. Q: How do I download skins? If you click the "Download" button on any skin's page, you'll be prompted to save it to a directory on your computer.

Intro to the Minecraft Skindex: Enter the Minecraft Metaverse in Style

1811 Dictionary in the Vulgar Tongue, by Francis Grose is part of HackerNoon’s Book Blog Post series. You can jump to any chapter in this book here: [ ]. Section J LINK TO TABLE OF LINK Section J JABBER. To talk thick and fast, as great praters usually do, to chatter like a magpye; also to speak a foreign language. He jabbered to me in his damned outlandish parlez vous, but I could not understand him; he chattered to me in French, or some other foreign language, but I could not understand him. JACK. A farthing, a small bowl serving as the mark for bowlers. An instrument for pulling off boots. JACK ADAMS. A fool. Jack Adams's parish; Clerkenwell. JACK AT A PINCH, A poor hackney parson. JACK IN A BOX, A sharper, or cheat. A child in the mother's womb. JACK IN AN OFFICE, An insolent fellow in authority. JACK KETCH. The hangman; vide DERRICK and KETCH. JACK NASTY FACE. A sea term, signifying a common sailor. JACK OF LEGS. A tall long-legged man; also a giant, said to be buried in Weston church, near Baldock, in Hertfordshire, where there are two stones fourteen feet distant, said to be the head and feet stones of his grave. This giant, says Salmon, as fame goes, lived in a wood here, and was a great robber, but a generous one; for he plundered the rich to feed the poor: he frequently took bread for this purpose from the Baldock bakers, who catching him at an advantage, put out his eyes, and afterwards hanged him upon a knoll in Baldock field. At his death he made one request, which was, that he might have his bow and arrow put into his hand, and on shooting it off, where the arrow fell, they would bury him; which being granted, the arrow fell in Weston churchyard. Above seventy years ago, a very large thigh bone was taken out of the church chest, where it had lain many years for a show, and was sold by the clerk to Sir John Tradescant, who, it is said, put it among the rarities of Oxford. JACK PUDDING. The merry andrew, zany, or jester to a mountebank. JACK ROBINSON. Before one could say Jack Robinson; a saying to express a very short time, originating from a very volatile gentleman of that appellation, who would call on his neighbours, and be gone before his name could be announced. JACK SPRAT. A dwarf, or diminutive fellow. JACK TAR. A sailor. JACK WEIGHT. A fat man. JACK WHORE. A large masculine overgrown wench. JACKANAPES. An ape; a pert, ugly, little fellow. JACKED. Spavined. A jacked horse. JACKMEN. See JARKMEN. JACKEY. Gin. JACOB. A soft fellow. A fool. JACOB. A ladder: perhaps from Jacob's dream. CANT. Also the common name for a jay, jays being usually taught to say, Poor Jacob! a cup of sack for Jacob. JACOBITES. Sham or collar shirts. Also partizans for the Stuart family: from the name of the abdicated king, i.e. James or Jacobus. It is said by the whigs, that God changed Jacob's name to Israel, lest the descendants of that patriarch should be called Jacobites. JADE. A term of reproach to women. JAGUE. A ditch: perhaps from jakes. JAIL BIRDS. Prisoners. JAKES. A house of office, a cacatorium. JAMMED. Hanged. CANT. JANIZARIES. The mob, sometimes so called; also bailiffs, their setters, and followers. JAPANNED. Ordained. To be japanned; to enter into holy orders, to become a clergyman, to put on the black cloth: from the colour of the japan ware, which is black. JARK. A seal. JARKMEN. Those, who fabricate counterfeit passes, licences, and certificates for beggars. JARVIS. A hackney coachman. JASON'S FLEECE. A citizen cheated of his gold. JAW. Speech, discourse. Give us none of your jaw; let us have none of your discourse. A jaw-me-dead; a talkative fellow. Jaw work; a cry used in fairs by the sellers of nuts. JAZEY. A bob wig. IDEA POT. The knowledge box, the head. See KNOWLEDGE BOX. JEFFY. It will be done in a jeffy; it will be done in a short space of time, in an instant. JEHU. To drive jehu-like; to drive furiously: from a king of Israel of that name, who was a famous charioteer, and mentioned as such in the Bible. JEM. A gold ring. CANT. JEMMY FELLOW. A smart spruce fellow. JEMMY. A crow. This instrument is much used by housebreakers. Sometimes called Jemmy Rook. JENNY. An instrument for lifting up the grate or top of a show-glass, in order to rob it. CANT. JERRYCUMMUMBLE. To shake, towzle, or tumble about. JERRY SNEAK. A henpecked husband: from a celebrated character in one of Mr. Foote's plays, representing a man governed by his wife. JESSAMY. A smart jemmy fellow, a fopling. JESIUT. See TO BOX THE JESUIT. JESUITICAL. Sly, evasive, equivocal. A jesuitical answer; an equivocal answer. JET. A lawyer. Autem jet; a parson. JEW. An over-reaching dealer, or hard, sharp fellow; an extortioner: the brokers formerly behind St. Clement's church in the Strand were called Jews by their brethren the taylors. JEW. A tradesman who has no faith, i.e. will not give credit. JEW BAIL. Insufficient bail: commonly Jews, who for a sum of money will bail any action whatsoever, and justify, that is, swear to their sufficiency; but, when called on, are not to be found. JEW'S EYE. That's worth a Jew's eye; a pleasant or agreeable sight: a saying taken from Shakespeare. JIBBER THE KIBBER. A method of deceiving seamen, by fixing a candle and lanthorn round the neck of a horse, one of whose fore feet is tied up; this at night has the appearance of a ship's light. Ships bearing towards it, run on shore, and being wrecked, are plundered by the inhabitants. This diabolical device is, it is said, practised by the inhabitants of our western coasts. JIG. A trick. A pleasant jig; a witty arch trick. Also a lock or door. The feather-bed jig; copulation. JIGGER. A whipping-post. CANT. JILT. A tricking woman, who encourages the addresses of a man whom she means to deceive and abandon. JILTED. Rejected by a woman who has encouraged one's advances. JINGLE BOXES. Leathern jacks tipped with silver, and hung with bells, formerly in use among fuddle caps. CANT. JINGLE BRAINS. A wild, thoughtless, rattling fellow. JINGLERS. Horse cosers, frequenting country fairs. JUG. See DOUBLE JUG. JUGGLER'S BOX. The engine for burning culprits in the hand. CANT. JUKRUM. A licence. JUMBLEGUT LANE. A rough road or lane. JUMP. The jump, or dining-room jump; a species of robbery effected by ascending a ladder placed by a sham lamp-lighter, against the house intended to be robbed. It is so called, because, should the lamp-lighter be put to flight, the thief who ascended the ladder has no means of escaping but that of jumping down. JUMPERS. Persons who rob houses by getting in at the windows. Also a set of Methodists established in South Wales. JUNIPER LECTURE. A round scolding bout. JURY LEG. A wooden leg: allusion to a jury mast, which is a temporary substitute for a mast carried away by a storm, or any other accident. SEA PHRASE. JURY MAST. A JOURNIERE mast; i.e. a mast for the day or occasion. JUST-ASS. A punning appellation for a justice. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Urbana, Illinois: Project Gutenberg. Retrieved April 2022 from Grose, Francis. 2004. 1881 Dictionary in the Vulgar Tongue. https://www.gutenberg.org/cache/epub/5402/pg5402.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at , located at . www.gutenberg.org https://www.gutenberg.org/policy/license.html

1811 Dictionary in the Vulgar Tongue: Section J

Everyone is all like, but let me you tell you something, I am single and ready to mingle. don't come back from space Jeff , In the beginning, no one thought Amazon could sell books online or become the most dominant ecommerce store of the Western world, but here we are. It took a lot of work! But now is Jeffy's time. Finally. I'm gonna do things for me. Enough of this customer-centric hogwash, it's Jeffy's time to shine! Hello world! I've created this account on HackerNoon to find love. DMs open.

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We started by following up on a hunch, but the survey results we are collecting are starting to feel much more sinister.¹ Hi there. You might remember my last about fake comments in the FCC proceeding for a project I did at . In the last couple of weeks since that post, I’ve been working day and night² as a member of the Truth in Public Comments (TiPC) project at the ³ here in SF. blog post net neutrality Metis Startup Policy Lab We wanted to uncover more facts beneath the suspicions so many others have raised. The best way was to take as direct a measurement as possible — to survey the commenters who provided an email address and ask whether they submitted the comment in the first place.⁴ Here are a few charts from survey results as of 8pm PT on December 10:⁵ The pro-repeal campaigns shown comprise most of the 8 million pro-repeal comments in the record. We are still working hard on the final report but I just wanted to share with you our preliminary results on each of the campaigns.⁵ On December 14, the FCC will hold a (perfunctory) vote to kill the net neutrality rule, and SPL has agreed to release these preliminary charts in the interests of getting timely information out to the public. Here is their on the issue. press release A couple more charts on response and bounceback rates. Huge discrepancy in response rates. The pro-net neutrality spam campaigns feel a lot less ‘planned’, e.g., no procurement of fake IDs. Stay tuned — SPL will be issuing a preliminary report as more results gathered and analyses and conclusions are confirmed. ¹ My own opinion. Although I am a volunteer leading the data and survey effort for this project at Startup Policy Lab, I’m speaking on my blog as an individual. ² Not ashamed to say that I slept four hours in a nap room at Metis SF on a Sunday night. ³ SPL does some great work on civic tech and other issues at the intersection of , policy and tech. It’s been tough pulling everything together on such short notice but they have been a steady ship in the storm. Sorry, Charles and Gina, for my frantic late night/early morning slack spam. law ⁴ Not the most glamorous data science work, but sometimes old-school methods get the job done. ⁵ Campaign details and aggregate stats on . this google spreadsheet ⁶ I should add a huge caveat that this information is provided without a detailed write-up of methodology and assumptions. That said, I was shocked to see the the stark divide in aggregate stats between pro-repeal and pro-net neutrality campaigns. Our report will give our methodology and assumptions. We will publish the email survey text that we used and will also be publishing relevant code and de-identified data for public verification.

Large-scale appropriation of Americans’ IDs suggested by Fake Pro-Repeal Net Neutrality Commenters’…

I used natural language processing techniques to analyze net neutrality comments submitted to the FCC from April-October 2017, and the results were disturbing. [Update on 11–29–2017: I’ve posted multiple datasets and my code containing enough for you to reproduce the analysis. Please share with the rest of us what else you find — *gets on soapbox* — a free internet will always be filled with competing narratives, but well-researched, reproducible data analyses can establish a ground truth and help cut through all of that. Look forward to seeing your analyses & there will be more data to come!] NY Attorney General Schneiderman and used in spam campaigns that support repealing . My research found at least 1.3 million pro-repeal comments, with suspicions about many more. In fact, the sum of fake pro-repeal comments in the proceeding may number in the millions. In this post, I will point out one particularly egregious spambot submission, make the case that there are likely many more pro-repeal spambots yet to be confirmed, and estimate the public position on net neutrality in the “organic” public submissions.¹ estimated that hundreds of thousands of Americans’ identities were stolen net neutrality fake Key Findings:² One pro-repeal spam campaign as unique grassroots submissions. used mail-merge to disguise 1.3 million comments There were likely multiple other campaigns aimed at injecting what may total pro-repeal comments into the system. several million It’s highly likely that of the truly unique comments³ were in favor of keeping net neutrality. more than 99% Breaking Down the Submissions Given the irregularities throughout the comment submission process, it was clear from the start that the data was going to be duplicative and messy. If I wanted to do the analysis without having to set up the tools and infrastructure typically used for “big data,” I needed to break down the 22M+ comments and 60GB+ worth of text data and metadata into smaller pieces.⁴ well documented Thus, I tallied up the many duplicate comments⁵ and arrived at 2,955,182 unique comments and their respective duplicate counts. I then mapped each comment into semantic space vectors⁶ and ran some clustering algorithms on the meaning of the comments.⁷ This method identified nearly 150 clusters of comment submission texts of various sizes.⁸ After clustering comment categories and removing duplicates, I found that less than 800,000 of the 22M+ comments submitted to the FCC (3-4%) could be considered truly unique. Here are the top 20 comment ‘campaigns’, accounting for a whopping 17M+ of the 22M+ submissions: The vast majority of FCC comments were submitted as exact duplicates or as part of letter-writing/spam campaigns. So how do we know which of these are legitimate public mailing campaigns, and which of these were bots? Identifying 1.3 Million Mail-Merged Spam Comments The first and largest cluster of pro-repeal documents was especially notable. Unlike the other clusters I found (which contained a lot of repetitive language) each of the comments here was unique; however, the tone, language, and meaning across each comment was largely uniform. The language was also a bit stilted. Curious to dig deeper, I used regular expressions⁹ to match up the words in the clustered comments: I found the term “People like me” particularly ironic. It turns out that there are 1.3 million of these. Each sentence in the faked comments looks like it was generated by a computer program. A mail merge swapped in a synonym for each term to generate unique-sounding comments.¹⁰ It was like mad-libs, except for . astroturf When laying just five of these side-by-side with highlighting, as above, it’s clear that there’s something fishy going on. But when the comments are scattered among 22+ million, often with vastly different wordings between comment pairs, I can see how it’s hard to catch. Semantic clustering techniques, and not typical string-matching techniques, did a great job at nabbing these. Finally, it was particularly chilling to see these spam comments all in one place, as they are exactly the type of policy arguments and language you expect to see in industry comments on the proposed repeal¹¹, or, these days, in the FCC Commissioner’s own statements lauding the repeal.¹² Pro-Repeal Comments were more Duplicative and in Much Larger Blocks But just because the largest block of pro-repeal submissions turned out to be a premediated and orchestrated spam campaign¹³, it doesn’t necessarily follow that there are many more pro-repeal spambots to be verified, right? As it turns out, the next two highest comments on the list (“In 2015, Chairman Tom Wheeler’s …” and “The unprecedented regulatory power the Obama Administration imposed …”) have already been as possible astroturf as well. picked out from previous reporting Going down the list, each comment cluster/duplicate would need its own investigation, which is beyond the scope of this post. We can, however, still gain an understanding of the distribution of comments by taking a broader view. Reprising the bar chart above breaking down the top FCC comments, let’s look at the top 300 comment campaigns that comprise an astonishing 21M+ of the 22M+ submissions¹⁴: Keep-Net Neutrality comments were much more likely to deviate from the form letter, and dominated in the long tail. From this chart we can see that the pro-repeal comments (there are approximately 8.6 million of them) are much more likely to be exact duplicates (dark red bars) and are submitted in much larger blocks. If even 25% of these pro-repeal comments are found to have been spam, that would still result in more than 2 million faked pro-repeal comments, each with an email address attached. Further verification should be done on the email addresses used to submit these likely spam comments. On the other hand, comments in favor of net neutrality were more likely to deviate from a form letter (light green, as opposed to dark green bars) and were much more numerous in the long tail. If the type, means of submission, and ‘spamminess’ of comments from both sides were equal, we would expect a roughly even distribution of light and dark, red and green, throughout the bars. This is evidently not the case here.¹⁵ Organic Public Comments: 99%+ Support Keeping Net Neutrality And what of the less than 800,000 comments submitted that were not a duplicate or clustered as part of a comment category? Does the trend of comments turning in favor of net neutrality continue in the long tail? It turns out allows us to take a representative sample and get a pretty good approximation of the population proportion and a confidence interval. ** **¹⁶ That results in an estimate of the population proportion at 99.7%. In fact, we are so near 100% pro net neutrality that the confidence interval goes outside of 100%.¹⁷ At the very minimum, we can conclude that the vast preponderance of individuals passionate enough about the issue to write up their own comment are for keeping net neutrality. old-school statistics After taking a 1000 comment random sample of the 800,000 organic comments and scanning through them, I was only able to find three comments that were clearly pro-repeal. Oh, and please do take a minute to scan through I’ve provided. Those are the comments of real people being affected by this decision, who speak most personally and devastatingly about its impacts: the samples I am 82, handicapped, and home bound, but not lonely, because I have the free internet. I can roam the world. use Facebook to visit family friends. I can sell my work on Etsy without fear of Amazon getting preference should the 2015 law be repealed. If you (The FCC) no longer had oversight, my ISP could raise its prices so that I couldn’t afford to have the Internet at all! I am relying on the FCC to protect me and others like me.¹⁸ Conclusion Public participation and civic engagement are fundamental to a functioning democracy. It’s scary to think that organic, authentic voices in the public debate — more than 99% of which are in favor of keeping net neutrality — are being drowned out by a chorus of spambots. We already live in a time of low faith in public institutions, and given these findings, I fear that the federal regulatory public comment process may be yet another public forum lost to spam and disinformation. ¹⁹ With the for keeping net neutrality, it’s irresponsible for the FCC majority to simply wave their hand and disregard public opinion in the , merely , or because . overwhelming actual public support latest draft order because of irregularities in the public record the public comments weren’t written in legalese FCC chairman Ajit Pai’s office not only needs to furnish the evidence sought by AG Schneiderman, they need to respond to the regarding the net neutrality public comments candidly and transparently, to restore public confidence in the FCC rulemaking process. FOIA requests Additional Notes: There have been some great analyses focused on the non-textual elements of the submissions, for example, their timing, the email addresses used, and other metadata. Shout out to the work of Jeffrey Fossett, who did in May that inspired this post and some of the methods used in the analysis, to , , and many other posts I studied in preparing this analysis. a first pass analysis of the partially submitted comments Chris Sinchok GravWell Let me know if you have any questions or would like access to the dataset I scraped from the FCC’s ECFS submission system — if enough folks request it, I may host the dataset on Google BigQuery so you can run SQL queries on the ~64 GB dataset on your own. here Footnotes: ¹ I.e., not from a spambot or part of an identified campaign. ² Full disclosure: I was a summer law clerk for Commissioner Clyburn in 2010, and though I greatly admire her recent work , the opinions and POV in this post are my own. championing net neutrality ³ Not clustered as part of a comment submission campaign, not a duplicate comment. ⁴ Data collected from beginning of submissions (April 2017) until Oct 27th, 2017. The long-running comment scraping script suffered from a couple of disconnections and I estimate that I lost ~50,000 comments because of it. Even though the Net Neutrality Public Comment Period ended on August 30, 2017, the FCC ECFS system continued to take comments afterwards, which were included in the analysis. ⁵ I used an md5 hash function, which had a and allowed me to (relatively) quickly find and count up duplicates. I tossed out submissions with no express comment text but otherwise did not do any other text preprocessing on the text before encoding and clustering in order to preserve artifacts in the text that may give clues as to the method of submission. low enough collision rate ⁶ A large proportion of these ~3 million “unique” comments were essentially duplicates — only differing by a few characters or words or having a different signature. In order to conclusively and exhaustively categorize these comments, I chose to group comments by meaning. Comments were turned into document vectors comprised of the average of all word vectors in the comment. The word vectors were obtained from , which uses the word vectors from the paper by . [ ] spaCy Levy and Goldberg (2014) Correction from Matthew Honnibal : spaCy now uses the GloVe vectors by Pennington et al. ⁷ I made two passes at clustering the document vectors. First with with a euclidean distance metric at a very low epsilon to identify obvious clusters [ ] and cull them out manually using a string signature. This left ~2 million unique comments. From that 2 million, I used on a 100,000 comment sample with cosine distance to identify ‘looser’ clusters, and then used to classify remaining comments as either within those identified clusters or as outliers. Removing duplicates, this resulted in less than 800,000 unique outlier “organic” comments. [ ] DBSCAN Update on 11–25–2017: After reviewing old code & to give slightly more detail, I used HAC to pick out the mad-lib clusters HDBSCAN [approximate_predict()](http://hdbscan.readthedocs.io/en/latest/prediction_tutorial.html) Correction: As HDBSCAN Author Leland McInnes notes below, cosine distances don’t yet play well with HDBSCAN — to be exact, I used the euclidean distance metric between l2-normalized doc vectors, which typically works well as a substitute. ⁸ Sized from the dozens to the millions. ⁹ Regular Expression in this . pastebin ¹⁰ This is because the combinations of comment configurations grows exponentially with each set of synonyms introduced. Also, to be precise, there were some mad-lib comments that were duplicated once, but not more than that. ¹¹ Page 3 of (submitted August 30, 2017) the Verizon Comments ¹² FCC Chairman Pai’s (published November 21, 2017) Statement re the Draft Order ¹³ While there are certainly other possible explanations for this set of results, I think should apply. More investigation into the timing and emails used for this particular campaign would provide more corroborating evidence. Occam’s Razor ¹⁴ Plotted on a log-scale so you can still see the color of the smaller bars. ¹⁵ As the author of the states: “[The evidence] forces us to conclude that either the very act of going to the FCC comment site and providing a comment is only attractive to those of a certain political leaning, or that the bulk submission information is full of lies.” Gravwell study ¹⁶ Pro-repeal comments are on lines 176, 228, 930 in the . There also appeared to be three net neutrality supporters that seemed confused about the terminology (lines 332, 366, 901) and one script kiddie (line 261). It’s possible I have missed one or two, and I’m happy to correct any mistakes in this comment set if you find them. pastebin ¹⁷ My more statistically-inclined colleague informs me that the central limit theorem breaks down at the extreme limits (where the population proportion is near 0% or 100% of a population), which I have taken his word/expertise for, for now, and will learn about later. [ ] Edit: I have found a good addition to this on a reddit comment . The interval is 99.12% to 99.90%, 19 times out of 20. ¹⁸ Line 102 in the . pastebin ¹⁹ [A final late addition: Lest I am unintentionally giving the wrong impression to folks who haven’t been following the net neutrality debate as closely, I want to be clear that there were suspicious campaigns from all sides of the debate from the text-only analysis; however, none were as numerous and as intentionally disguised as the 1.3M ‘unique’ comments identified in the post.]

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