Alleois in the Enterprise Collaboration Industry

Alleo

alleo

The article demonstrates the idea of using memory allocations for vibrant and high-performance applications. There are majorly two types of memory allocation i.e. stack vs heap which plays a role in how your application uses resources and, further, how fast and responsive the application can be. Learning Objectives What is heap allocation? What is stack allocation? Limiting the Use of Heap-Allocated Objects Prerequisites for Developers Basic understanding of C# programming language. 30 Day .Net Challenge Getting Started What is heap allocation? The heap memory is primarily used for dynamic allocation, where the size and lifespan of the allocation are not predicted at the compile time. Reference types instances (like objects and arrays in C#) are stored on the heap. What is stack allocation? The stack is a section of memory that stores value types and pointers to heap-allocated objects. Memory allocation on the stack is fast because it involves merely moving the stack pointer. Limiting the Use of Heap-Allocated Objects Whenever possible, opt for stack allocation or the use of value types to minimize the need for garbage collection. Inefficient Heap Allocation The following method creates a new string object on the heap each time the method is called, which will call the Garbage Collection each time too. private string GetUserName(int index)
{
    // Inefficient: Creates a new string object on the heap
    return new string($"User{index}".ToCharArray());
} Efficient Allocation By returning the interpolated string without newkeyword avoids unnecessary heap allocation and reduces the impact on garbage collection, which leads to better performance. private string GetUserName(int index)
{
    // Efficient: Avoids unnecessary heap allocation
    return $"User{index}";
} Create another class named StackVsHeap and add the following code snippet public static class StackVsHeap
{
    public static string InefficientMethod(int index)
    {
        // Inefficient: Creates a new string object on the heap
        return new string($"User{index}".ToCharArray());
    }

    public static string EfficientMethod(int index)
    {
        // Efficient: Avoids unnecessary heap allocation
        return $"User{index}";
    }
} Execute from the main method as follows #region Day 19: Stack vs. Heap Allocation
static string ExecuteDay19()
{
    StackVsHeap.InefficientMethod(0);
    StackVsHeap.EfficientMethod(0);
    return "Executed Day 19 successfully..!!";
}

#endregion Console output User0
User0 Complete Code on GitHub GitHub — ssukhpinder/30DayChallenge.Net C# Programming🚀 Thank you for being a part of the C# community! Before you leave: Follow us: | | | Visit our other platforms: More content at Youtube X LinkedIn Dev.to GitHub C# Programming

The 30-Day .NET Challenge—Day 19: Stack vs. Heap Allocation

X Corp. v. Center for Countering Digital Hate, INC. Court Filing, retrieved on March 25, 2024 is part of . You can jump to any part in this filing . This part is 16 of 19. HackerNoon’s Legal PDF Series here 1. Causation CCDH argues that X Corp. fails to allege that CCDH’s conduct caused Brandwatch to breach its agreement with X Corp. MTD&S at 23–24. The Court agrees. Both tort claims envision that the defendant has done something to “push[] a contracting party to act in a way that disrupts the contract.” Id. at 24 (citing Jenni Rivera Enters., LLC v. Latin World Ent. Holdings, Inc., 249 Cal. Rptr. 3d 122, 129 (Cal. Ct. App. 2019) (defendant induced counterparty to breach a nondisclosure agreement); Savage v. Pac. Gas & Elec. Co., 26 Cal. Rptr. 2d 305, 315 (Cal. Ct. App. 1993) (defendant persuaded plaintiff’s employer to terminate employment agreement); SCEcorp v. Super. Ct. of San Diego Cnty., 4 Cal. Rptr. 2d 372, 373–74, 378 (Cal. Ct. App. 1992) (defendant forced counterparty to abandon merger)). X Corp. does not allege that CCDH got Brandwatch to do anything at all. X Corp. alleges that Brandwatch agreed to keep Twitter’s content secure, FAC ¶ 31, that CCDH’s “obtain[ing] access to and access[ing] the Licensed Materials improperly and without authorization” was “unknown to Brandwatch . . . until recently,” id. ¶ 41, and that CCDH’s access “prevented Brandwatch from performing” because it meant that “Brandwatch failed to secure the data . . . according to the terms of the agreements,” id. ¶ 93. As CCDH argues, those allegations “show that any breach occurred independently of (and by necessity, before) [CCDH’s] actions.” MTD&S at 24 (adding: “the access did not cause the breach, the breach caused the access.”). X Corp.’s response is that “the access is the breach.” Opp’n at 30. In other words, Brandwatch agreed to keep the Licensed Materials secure, and by allowing CCDH to access the Licensed Materials, Brandwatch necessarily—and simultaneously—breached its agreement to keep the Licensed Materials secure. The Court rejects that tortured reasoning. Any failure by Brandwatch to secure the Licensed Materials was a precondition to CCDH’s access. In addition, to the extent that X Corp. maintains that CCDH need not have done anything to impact Brandwatch’s behavior, then it is seeking to hold CCDH liable for breaching a contract to which it was not a party. That does not work either. See Tri-Continent Int’l Corp. v. Paris Sav. & Loan Ass’n, 16 Cal. Rptr. 2d 508, 511 (Cal. Ct. App. 1993) (a plaintiff “cannot assert a claim for breach of contract against one who is not a party to the contract.”). Causation is therefore one basis for striking the tort claims. Continue Reading . Here About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on March 25, 2024, from is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. storage.courtlistener

Debating Causation in the X Lawsuit Against CCDH: Impact on Tort Allegations

X Corp. v. Center for Countering Digital Hate, INC. Court Filing, retrieved on March 25, 2024 is part of . You can jump to any part in this filing . This part is 10 of 19. HackerNoon’s Legal PDF Series here B. Breach of Contract Claim The complaint’s first cause of action is for breach of contract. FAC ¶¶ 73–79. To state a claim for breach of contract, a plaintiff must allege (1) the existence of a contract, (2) plaintiff’s performance or excuse for nonperformance, (3) defendant’s breach, and (4) resulting damages to the plaintiff. See Oasis W. Realty, 250 P.3d at 1121. X Corp. alleges that X Corp. and CCDH U.S. are parties to the ToS, which explicitly prohibits “‘scraping the Services without the prior consent of Twitter.’” FAC ¶¶ 74, 75. X Corp. further alleges that it fully performed its obligations, but that CCDH U.S. violated the ToS by scraping the X platform, and that CCDH then “mischaracterized the data it obtained by unlawfully scraping in its reports and articles, in efforts to claim X is overwhelmed with harmful conduct, and support CCDH’s call to companies to stop advertising on X.” Id. ¶¶ 76–78. X Corp. notes that CCDH’s February 9, 2023 report admits that “‘[t]o gather tweets from each of the ten reinstated accounts, [CCDH’s] researchers used the social media web-scraping tool SNScrape, which utilizes Twitter’s search function to enable data collection.’” Id. ¶ 77. And X Corp. alleges that “[a]s a direct and proximate result of CCDH U.S.’s breaches of the ToS in scraping X, X Corp. has suffered monetary and other damages in the amount of at least tens of millions of dollars.” Id. ¶ 78. The “at least tens of millions of dollars” of damages derives from companies pausing paid advertising on the X platform in response to CCDH’s “allegations against X Corp. and X regarding hate speech and other types of content on X.” Id. ¶ 70. CCDH argues that X Corp. fails to state a breach of contract claim, for three reasons: (1) X Corp. has failed to adequately allege a breach; (2) if the ToS’s anti-scraping provision applies, it violates public policy; and (3) X Corp. has failed to adequately allege recoverable damages. MTD&S at 9–18. The Court concludes that CCDH’s argument about damages is persuasive, and does not reach CCDH’s other arguments. CCDH maintains that X Corp. fails to adequately allege damages resulting from CCDH’s alleged scraping of the X platform because: (a) under state contract law, X Corp.’s lost advertising revenue is not recoverable; (b) constitutional law bars X Corp. from using a non-defamation cause of action to recover reputational damages; and (c) allowing this cause of action, in which X Corp. seeks tens of millions of dollars, to stand would subject CCDH to “significant costs of enduring discovery and litigation . . . against a well-resourced adversary with every incentive to impose crushing burdens on the CCDH Defendants.” Id. at 15–18. That last argument is emotional rather than legal; while the Court is not blind to the David and Goliath dynamic here, the law does not bar big companies from suing small nonprofits, so long as the suit is otherwise up to snuff. This order therefore addresses only CCDH’s arguments based on state contract law and constitutional law. Continue Reading . Here About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on March 25, 2024, from is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. storage.courtlistener

X (Formerly Twitter) Hits CCDH With Breach of Contract Allegations

X Corp. v. Center for Countering Digital Hate, INC. Court Filing, retrieved on March 25, 2024 is part of . You can jump to any part in this filing . This part is 8 of 19. HackerNoon’s Legal PDF Series here 2. “Arising from” In addition, X Corp.’s claims arise from protected conduct. To determine whether a claim or claims arise from protected activity, courts are to look to “the conduct that constitutes the specific act of wrongdoing challenged by the plaintiff.” Jordan-Benel v. Universal City Studios, Inc., 859 F.3d 1184, 1190 (9th Cir. 2017). “A defendant in an ordinary private dispute cannot take advantage of the antiSLAPP statute simply because the complaint contains some references to speech or petitioning activity by the defendant.” Sansoe v. Ford Motor Co., 668 Fed. Appx. 718, 719 (9th Cir. 2016) (quoting People ex rel. Fire Ins. Exch. v. Anapol, 211 Cal. App. 4th 809 (2012)). In addition, “the mere fact an action was filed after protected activity took place does not mean it arose from that activity.” City of Cotati v. Cashman, 29 Cal. 4th 69, 76– 77 (2002). In Jordan-Benel, the plaintiff was a screenwriter who alleged that defendant production companies’ failure to compensate and credit him for a script constituted a breach of contract. Id. at 1187, 1189. The defendants brought an anti-SLAPP motion, arguing that the contract claim arose from their free-speech activity of producing a film. Id. at 1190. The Ninth Circuit agreed with the plaintiff, concluding that the specific wrongful act that gave rise to the claim was the failure to pay. Id. The court explained that even if the cause of action was triggered by protected activity—the release of the film—that does not mean that the action arose from it: “even if a defendant engages in free speech activity that is relevant to a claim, that does not necessarily mean such activity is the basis for the claim.” Id.; see also Martinez v. Metabolife Internat., Inc., 113 Cal. App. 4th 181, 187 (2003) (“[W]hen the allegations referring to arguably protected activity are only incidental to a cause of action based essentially on nonprotected activity, collateral allusions to protected activity should not subject the cause of action to the anti-SLAPP statute.”). X Corp. argues that just as the production of the film was not the specific act that gave rise to the claim in Jordan-Benel, CCDH’s publication of its articles and reports is not the specific act of wrongdoing at issue here. See Opp’n at 10–11 (“CCDH’s alleged ‘speech’ is not the wrong complained of—its wanton breach of contract and illegal access of data are.”). But even accepting that the conduct that forms the specific wrongdoing in the state law claims is CCDH’s illegal access of X Corp. data, that conduct (scraping the X platform and accessing the Brandwatch data using ECF’s login credentials) is newsgathering—and claims based on newsgathering arise from protected activity. See Iloh, 94 Cal. App. 5th at 956–57. It is also just not true that the complaint is only about data collection. See Reply at 3 (arguing that X Corp.’s contention that its “claims arise from ‘illegal access of data,’ as opposed to speech,” is the “artifice” at “the foundation of [this] whole case.”) (quoting Opp’n at 10). It is impossible to read the complaint and not conclude that X Corp. is far more concerned about CCDH’s speech than it is its data collection methods. In its first breath, the complaint alleges that CCDH cherry-picks data in order to produce reports and articles as part of a “scare campaign” in which it falsely claims statistical support for the position that the X platform “is overwhelmed with harmful content” in order “to drive advertisers from the X platform.” See FAC ¶ 1. Of course, there can be no false claim without communication. Indeed, the complaint is littered with allegations emphasizing CCDH’s communicative use of the acquired data. See, e.g., id. ¶¶ 17–20 (reports/articles are based on “flawed ‘research’ methodologies,” which “present an extremely distorted picture of what is actually being discussed and debated” on the X platform, in order to “silence” speech with which CCDH disagrees); id. ¶ 43 (CCDH “used limited, selective, and incomplete data from that source . . . that CCDH then presented out of context in a false and misleading manner in purported ‘research’ reports and articles.”), id. ¶ 56 (“CCDH’s reports and articles . . . have attracted attention in the press, with media outlets repeating CCDH’s incorrect assertions that hate speech is increasing on X.”). X Corp. is correct that it has not brought a claim for defamation. See Opp’n at 10; FAC. It insists that that choice demonstrates that it is not really complaining about CCDH’s speech. Opp’n at 10. CCDH argues that X Corp.’s decision not to include a defamation claim is evidence that X Corp. “cannot allege that the CCDH Defendants said anything knowingly false, nor does it wish to invite discovery on the truth about the content on its platform.” MTD&S at 2; see also ACLU Br. at 1 (“X Corp. attempts to disguise a nonviable defamation claim as a breach of contract claim to retaliate against a nonprofit that provided the public with information critical of X Corp.”). Whatever X Corp. could or could not allege, it plainly chose not to bring a defamation claim.[10] As the Court commented at the motion hearing, that choice was significant. Tr. of 2/29/24 Hearing at 62:6–10. It is apparent to the Court that X Corp. wishes to have it both ways—to be spared the burdens of pleading a defamation claim, while bemoaning the harm to its reputation, and seeking punishing damages[11] based on reputational harm. For the purposes of the anti-SLAPP motion, what X Corp. calls its claims is not actually important. The California Supreme Court has held “that the anti-SLAPP statute should be broadly construed.” Martinez, 113 Cal. App. 4th at 187 (citing Equilon Enters. v. Consumer Cause, Inc., 29 Cal. 4th 53, 60 n.3 (2002)). Critically, “a plaintiff cannot avoid operation of the anti-SLAPP statute by attempting, through artifices of pleading, to characterize an action as a ‘garden variety breach of contract [or] fraud claim’ when in fact the liability claim is based on protected speech or conduct.” Id. at 188 (quoting Navellier, 29 Cal. 4th at 90–92); see also Baral v. Schnitt, 1 Cal. 5th 376, 393 (2016) (“courts may rule on plaintiffs’ specific claims of protected activity, rather than reward artful pleading”); Navellier, 29 Cal. 4th at 92 (“conduct alleged to constitute breach of contract may also come within constitutionally protected speech or petitioning. The anti-SLAPP statute’s definitional focus in not the form of the plaintiff’s cause of action[.]”) Collondrez v. City of Rio Vista, 61 Cal. App. 5th 1039 (2021), is a recent example of a court disregarding the name of a claim to assess its content. In that case, a former police officer brought suit for breach of contract and intentional interference with prospective economic advantage because his former employer disclosed information from his personnel file without giving him notice as required by contract. Id. at 1044–46. The court held that the claims nonetheless arose from protected speech, explaining that “we disregard [a claim’s] label and instead examine its gravamen.” Id. at 1051, 1048 (cleaned up). It then concluded that “the harmful act at the heart of the complaint, the act that allegedly cost [the plaintiff] his [new job] and resulted in other economic and emotional harm, is the publication of his personnel information.” Id. at 1049. Here, even though X Corp. did not include a cause of action explicitly premised on CCDH’s speech, as in Collondrez, speech is a harmful act at the heart of the complaint. X Corp. insists that that is not so, arguing that “CCDH’s actions caused harm independent of any alleged protected activities.” Opp’n at 11. It asserts that “[i]f CCDH carried out all the same illegal activities, but stopped just short of publishing the February 9, 2023 report, X Corp. would maintain the very same valid claims against it.” Opp’n at 11; see also id. at 11–12 (citing Kovalenko v. Kirkland & Ellis LLP, No. 22-cv-5990-HSG, 2023 WL 5444728, at *3 (N.D. Cal. Aug. 23, 2023) (“The question is whether the challenged allegations ‘supply a necessary element’ of a claim.”)). The Court disagrees— and not because it is impossible to imagine that X Corp. would have been motivated to bring suit had CCDH not spoken. Each of the state law causes of action—breach of contract, intentional interference with contractual relations, and inducing breach of contract—require as an element a showing of damages. See Oasis W. Realty, LLC v. Goldman, 250 P.3d 1115, 1121 (Cal. 2011) (“the elements of a cause of action for breach of contract are (1) the existence of the contract, (2) plaintiff’s performance or excuse for nonperformance, (3) defendant’s breach, and (4) the resulting damages to the plaintiff.”) (citing Reichert v. General Ins. Co., 68 Cal. 2d 822, 830 (1968)); United Nat’l Maint., Inc. v. San Diego Convention Ctr., Inc., 766 F.3d 1002, 1006 (9th Cir. 2014) (“the elements for the tort of intentional interference with contractual relations are ‘(1) a valid contract between plaintiff and a third party; (2) defendant’s knowledge of this contract; (3) defendant’s intentional acts designed to induce a breach or disruption of the contractual relationship; (4) actual breach or disruption of the contractual relationship; and (5) resulting damage.’”) (quoting Pac. Gas & Elec. Co. v. Bear Stearns & Co., 50 Cal.3d 1118 (1990)); Shamblin v. Berge, 166 Cal. App. 3d 118, 122–23 (1985) (inducement to breach a contract “requires that a plaintiff prove: ‘(1) he had a valid and existing contract [with a third party]; (2) . . . defendant had knowledge of the contract and intended to induce its breach; (3) the contract was in fact breached by the contracting party; (4) the breach was caused by . . . defendant’s unjustified or wrongful conduct; and (5) . . . damage[s] [were suffered as a result].’”) (quoting Dryden v. TriValley Growers, 65 Cal. App. 3d 990, 995 (1977)). X Corp.’s many allegations about CCDH’s speech do more than add color to a complaint about data collection—they are not “incidental to a cause of action based essentially on nonprotected activity.” See Martinez, 113 Cal. App. 4th at 187. Instead, the allegations about CCDH’s misleading publications provide the only support for X Corp.’s contention that it has been harmed. See FAC ¶ 78 (breach of contract claim: alleging that CCDH “mischaracterized the data . . . in efforts to claim X is overwhelmed with harmful conduct, and support CCDH’s call to companies to stop advertising on X. . . . As a direct and proximate result of CCDH’s breaches of the ToS in scraping X, X has suffered monetary and other damages in the amount of at least tens of millions of dollars”); ¶¶ 92– 93 (intentional interference claim: alleging that Defendants “intended for CCDH to mischaracterize the data regarding X in the various reports and articles . . . to support Defendants’ demands for companies to stop advertising on X” and that “[a]s a direct and proximate result of Defendants intentionally interfering with the Brandwatch Agreements . . . X Corp. has suffered monetary and other damages of at least tens of millions of dollars”); ¶¶ 98–99 (inducing breach of contract claim: alleging that “X Corp. was harmed and suffered damages as a result of Defendants’ conduct when companies paused or refrained from advertising on X, in direct response to CCDH’s reports and articles” and that “[a]s a direct and proximate result of Defendants inducing Brandwatch to breach the Brandwatch Agreements . . . X Corp. has suffered monetary and other damages in the amount of at least tens of millions of dollars.”). The “at least tens of millions of dollars” that X Corp. seeks as damages in each of those claims is entirely based on the allegation that companies paused paid advertising on the X platform in response to CCDH’s “allegations against X Corp. and X regarding hate speech and other types of content on X.” See id. ¶ 70. As CCDH says, “X Corp. alleges no damages that it could possibly trace to the CCDH Defendants if they had never spoken at all.” Reply at 3. Indeed, X Corp. even conceded at the motion hearing that it had not alleged damages that would have been incurred if CCDH “had scraped and discarded the information,” or scraped “and never issued a report, or scraped and never told anybody about it.” See Tr. of 2/29/24 Hearing at 7:22–8:3. The element of damages in each state law claim therefore arises entirely from CCDH’s speech. See Bonni v. St. Joseph Health Sys., 491 P.3d 1058, 1069–70 (Cal. 2021) (“a claim is subject to an anti-SLAPP motion to strike if its elements arise from protected activity.”). Accordingly, the state law claims arise from CCDH’s actions—its newsgathering and writing of reports/articles—in furtherance of CCDH’s free speech rights. Continue Reading . Here [10] At the motion hearing, X Corp. asserted that it was “not trying to avoid defamation” and claimed to have “pleaded falsity” in paragraph 50 of the complaint. Tr. of 2/29/24 Hearing at 59:20–23. In fact, paragraph 50 did not allege falsity, or actual malice, though it used the word “incorrect.” See FAC ¶ 50 (“incorrect implications . . . that hate speech viewed on X is on the rise” and “incorrect assertions that X Corp. ‘doesn’t care about hate speech’”). When the Court asked X Corp. why it had not brought a defamation claim, it responded rather weakly that “to us, this is a contract and intentional tort case,” and “we simply did not bring it.” Tr. of 2/29/24 Hearing at 60:1–12; see also id. at 60:21–22 (“That’s not necessarily to say we would want to amend to bring a defamation claim.”). [11] If there is any question about the “punishing” part, X Corp. filed a similar suit, not before this Court, in November of 2023 against Media Matters, another non-profit media watchdog, for “reporting on ads from major brands appearing next to neo-Nazi content.” PPP Br. at 10. Prior to doing so, Musk threatened a “thermonuclear lawsuit” against Media Matters. Id. (quoting Elon Musk (@elonmusk), X (Nov. 18, 2023, 2:01 AM), https://twitter.com/elonmusk/status/1725771191644758037 [https://perma.cc/K8SZM33S]). Musk’s post also claimed, remarkably, that the lawsuit was furthering X Corp.’s efforts “to protect[] free speech.” See Elon Musk (@elonmusk), X (Nov. 18, 2023, 2:01 AM), https://twitter.com/elonmusk/status/1725771191644758037 [https://perma.cc/K8SZM33S]. About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on March 25, 2024, from is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. storage.courtlistener

X Files Lawsuit Against Center for Countering Digital Hate, Alleging Speech Suppression Tactics 

Elon Musk's X Lawsuit Against Anti-Hate Group, CCDH, Alleging Speech Suppression Tactics 

United States v. Apple INC Court Filing, retrieved on March 21, 2024 is part of . You can jump to any part in this filing . This part is 24 of 25. HackerNoon’s Legal PDF Series here F. Sixth Claim for Relief: Violations of Wisconsin State Law 229. Plaintiff State of Wisconsin repeats and re-alleges and incorporates by reference every paragraph and allegation in this Complaint as if fully set forth herein. 230. The aforementioned practices by Apple violate Wisconsin’s Antitrust Act, Wis. Stat. Ch. § 133.03 et seq. These violations substantially affect the people of Wisconsin and have impacts within the State of Wisconsin. 231. Plaintiff State of Wisconsin, through its Attorney General and under its antitrust enforcement authority in Wis. Stat. Ch. 133, is entitled to all remedies available under Wis. Stat. §§ 133.03, 133.16, 133.17, and 133.18. Continue Reading . Here About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on March 21, 2024, from is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. justice.gov

Apple Faces Allegations in Wisconsin: Accused of Antitrust Violations Impacting Consumers

United States v. Apple INC Court Filing, retrieved on March 21, 2024 is part of . You can jump to any part in this filing . This part is 23 of 25. HackerNoon’s Legal PDF Series here E. Fifth Claim for Relief: Violation of the New Jersey Antitrust Act (Monopoly Maintenance) 224. Plaintiff State of New Jersey repeats and realleges and incorporates by reference each and every preceding paragraph and allegation of this Complaint as if fully set forth herein. 225. The New Jersey Antitrust Act, N.J.S.A. 56:9-4(a), states: “It shall be unlawful for any person to monopolize, or attempt to monopolize, or to combine or conspire with any person or persons, to monopolize trade or commerce in any relevant market within this State.” 226. In the operation of its business, Apple engaged in numerous commercial practices that violate the New Jersey Antitrust Act, N.J.S.A. 56:9-1 to -19, including monopolizing or attempting to monopolize trade or commerce in the smartphone market and the performance smartphone market within the State of New Jersey, in violation of N.J.S.A. 56:9-4. 227. Each violation of the New Jersey Antitrust Act by Apple constitutes a separate unlawful practice and violation, under N.J.S.A. 56:9-16. 228. Plaintiff State of New Jersey seeks all remedies available under the New Jersey Antitrust Act, N.J.S.A. 56:9-1 to -19, including, without limitation, the following: (a) injunctive and other equitable relief, pursuant to N.J.S.A. 56:9-7 and N.J.S.A.56:9-10(a); and (b) other remedies as the Court may deem appropriate and the interests of justice may require. Continue Reading . Here About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on March 21, 2024, from is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. justice.gov

New Jersey State Enters Legal Fray: Alleges Apple Violated Antitrust Laws with Monopoly Maintenance

United States v. Apple INC Court Filing, retrieved on March 21, 2024 is part of . You can jump to any part in this filing . This part is 21 of 25. HackerNoon’s Legal PDF Series here C. Third Claim for Relief: Monopolization of the Smartphone Market in the United States in Violation of Sherman Act § 2 211. Plaintiffs incorporate the allegations of paragraphs 1 through 210 above. 212. Smartphones in the United States is a relevant antitrust market, and Apple has monopoly power in that market. 213. Apple has willfully monopolized the smartphone market in the United States through an exclusionary course of conduct and the anticompetitive acts described herein. Each of Apple’s actions individually and collectively increased, maintained, or protected its smartphone monopoly. 214. Apple’s anticompetitive acts include, but are not limited to, its contractual restrictions against app creation, distribution, and access to APIs that have impeded apps and technologies including, but not limited to, super apps, cloud streaming, messaging, wearables, and digital wallets. The areas identified in this complaint reflect a non-exhaustive list of recent anticompetitive acts but as technology advances, both the technologies impeded and the specific manner of impediment may shift in response to technological and regulatory change consistent with Apple’s past conduct. 215. While each of Apple’s acts is anticompetitive in its own right, Apple’s interrelated and interdependent actions have had a cumulative and self-reinforcing effect that has harmed competition and the competitive process. 216. Apple’s anticompetitive acts have had harmful effects on competition and consumers. 217. Apple’s exclusionary conduct lacks a procompetitive justification that offsets the harm caused by Apple’s anticompetitive and unlawful conduct. Continue Reading . Here About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on March 21, 2024, from is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. justice.gov

United States Alleges Apple's Monopolization of US Smartphone Market Violates Sherman Act

USA v. Samuel Bankman-Fried Court Filing, retrieved on March 15, 2024 is part of . You can jump to any part in this filing . This part is 12 of 33. HackerNoon’s Legal PDF Series here C. The Defendant’s Perjury Bankman-Fried also obstructed justice by giving false testimony during the trial. Among other things, and as discussed further below, Bankman-Fried falsely testified that he did not know about Alameda spending customer deposits, that he did not know until late 2022 that FTX’s code features were being improperly used to take customer money, and that he thought in November 2022 that his tweets were accurate and not misleading. Continue Reading . Here About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on March 15, 2024, from is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. storage.courtlistener

Bankman-Fried Faces Perjury Allegations for Providing False Testimony in Court

This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license.
Authors:
(1) Cristina España-Bonet, DFKI GmbH, Saarland Informatics Campus. Table of Links Abstract and Intro
Corpora Compilation
Political Stance Classification
Summary and Conclusions
Limitations and Ethics Statement
Acknowledgments and References
A. Newspapers in OSCAR 22.01
B. Topics
C. Distribution of Topics per Newspaper
D. Subjects for the ChatGPT and Bard Article Generation
E. Stance Classification at Article Level
F. Training Details 5.1 Limitations We are assuming that All media sources have an editorial line and an associated bias, and we treat the ILM as any other media source. We do not consider the possibility of a ChatGPT or Bard article being unbiased. This is related to the distant supervision method used to gather the data that currently allows for a binary political stance annotation. Since manually annotating hundreds of thousands of articles with political biases in a truly multilingual setting seems not possible in the foreseeable future, we decided to implement a completely data-based method and study its language and culture transfer capabilities. Using distant supervision for detecting the political stance at article level is a delicate topic though. First, because the same newspaper can change ideology over time. Second, and this is more related to the content of an individual article, non-controversial subjects might not have a bias. Even in cases where bias exists, there is a spectrum ranging from the extreme Left to the extreme Right, rather than a clear-cut division between the two ideologies. In order to quantify and if possible mitigate the current limitations, we plan to conduct a stylistic analysis of the human-annotated corpora (Baly et al., 2020; Aksenov et al., 2021) and compare it to our semi-automatically annotated corpus. As a follow-up of this work, we will perform a stylistic analysis of the ILM-generated texts too as a similar style between the training data and these texts is needed to ensure good generalisation and transfer capabilities. 5.2. Ethics Statement We use generative language models, ChatGPT and Bard, to create our test data. Since we deal with several controversial subjects (death penalty, sexual harassment, drugs, etc.) the automatic generation might produce harmful text. The data presented here has not undergone any human revision. We analyse and provide the corpus as it was generated, along with the indication of the systems version used. This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license. Authors: (1) Cristina España-Bonet, DFKI GmbH, Saarland Informatics Campus. This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license. Authors: Authors: (1) Cristina España-Bonet, DFKI GmbH, Saarland Informatics Campus. Table of Links Abstract and Intro Corpora Compilation Political Stance Classification Summary and Conclusions Limitations and Ethics Statement Acknowledgments and References A. Newspapers in OSCAR 22.01 B. Topics C. Distribution of Topics per Newspaper D. Subjects for the ChatGPT and Bard Article Generation E. Stance Classification at Article Level F. Training Details Abstract and Intro Abstract and Intro Corpora Compilation Corpora Compilation Political Stance Classification Political Stance Classification Summary and Conclusions Summary and Conclusions Limitations and Ethics Statement Limitations and Ethics Statement Acknowledgments and References Acknowledgments and References A. Newspapers in OSCAR 22.01 A. Newspapers in OSCAR 22.01 B. Topics B. Topics C. Distribution of Topics per Newspaper C. Distribution of Topics per Newspaper D. Subjects for the ChatGPT and Bard Article Generation D. Subjects for the ChatGPT and Bard Article Generation E. Stance Classification at Article Level E. Stance Classification at Article Level F. Training Details F. Training Details 5.1 Limitations We are assuming that All media sources have an editorial line and an associated bias , and we treat the ILM as any other media source. We do not consider the possibility of a ChatGPT or Bard article being unbiased. This is related to the distant supervision method used to gather the data that currently allows for a binary political stance annotation. Since manually annotating hundreds of thousands of articles with political biases in a truly multilingual setting seems not possible in the foreseeable future, we decided to implement a completely data-based method and study its language and culture transfer capabilities. All media sources have an editorial line and an associated bias Using distant supervision for detecting the political stance at article level is a delicate topic though. First, because the same newspaper can change ideology over time. Second, and this is more related to the content of an individual article, non-controversial subjects might not have a bias. Even in cases where bias exists, there is a spectrum ranging from the extreme Left to the extreme Right, rather than a clear-cut division between the two ideologies. In order to quantify and if possible mitigate the current limitations, we plan to conduct a stylistic analysis of the human-annotated corpora (Baly et al., 2020; Aksenov et al., 2021) and compare it to our semi-automatically annotated corpus. As a follow-up of this work, we will perform a stylistic analysis of the ILM-generated texts too as a similar style between the training data and these texts is needed to ensure good generalisation and transfer capabilities. 5.2. Ethics Statement We use generative language models, ChatGPT and Bard, to create our test data. Since we deal with several controversial subjects (death penalty, sexual harassment, drugs, etc.) the automatic generation might produce harmful text. The data presented here has not undergone any human revision. We analyse and provide the corpus as it was generated, along with the indication of the systems version used.

Multilingual Coarse Political Stance Classification of Media: Limitations & Ethics Statement

মিডিয়ার বহুভাষিক মোটা রাজনৈতিক অবস্থানের শ্রেণীবিভাগ: সীমাবদ্ধতা এবং নীতিশাস্ত্রের বিবৃতি

Mehrsprachige grobe politische Haltung Klassifizierung von Medien: Einschränkungen und Ethikerklärung

Postura política burda multilingüe Clasificación de los medios: limitaciones y declaración de ética

Classification multilingue grossière des positions politiques des médias : limites et déclaration éthique

बहुभाषी असभ्य राजनीतिक रुख मीडिया का वर्गीकरण: सीमाएँ और नैतिकता वक्तव्य

多言語によるメディアの粗い政治的立場の分類：制限と倫理声明

미디어의 다국어 거친 정치적 입장 분류: 한계 및 윤리 선언문

Classificação multilíngue da postura política grosseira da mídia: limitações e declaração de ética

Многоязычная грубая классификация СМИ по политической позиции: ограничения и этическое заявление

Medyanın Çok Dilli Kaba Siyasi Duruş Sınıflandırması: Sınırlamalar ve Etik Beyanı

Phân loại lập trường chính trị thô sơ đa ngôn ngữ của phương tiện truyền thông: Hạn chế và tuyên bố đạo đức

多语言粗略政治立场媒体分类：限制与道德声明

This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license.
Authors:
(1) Cristina España-Bonet, DFKI GmbH, Saarland Informatics Campus. Table of Links Abstract and Intro
Corpora Compilation
Political Stance Classification
Summary and Conclusions
Limitations and Ethics Statement
Acknowledgments and References
A. Newspapers in OSCAR 22.01
B. Topics
C. Distribution of Topics per Newspaper
D. Subjects for the ChatGPT and Bard Article Generation
E. Stance Classification at Article Level
F. Training Details 4. Summary and Conclusions Media sources have an editorial line and an associated bias. Getting rid of political biases is difficult for humans, but being aware of them helps us getting a global view of news. Biases are sometimes clear and/or appear in form of harmful text, but sometimes are subtle and difficult to detect. These subtle hidden biases are potentially dangerous and lead to manipulation whenever we are not aware of them. In this work, we systematically studied the subtle political biases behind ChatGPT and Bard, those that appear without assigning any persona role (Deshpande et al., 2023). We showed that ChatGPT’s orientation changes with time and it is different across languages. Between Feb and Aug 2023, ChatGPT transitioned from a Left to Neutral political orientation, with a Right-leaning period in the middle for English and Spanish. The evolution for Bard cannot be studied yet. Its current version as of Aug 2023 consistently shows Left-leaning for the 4 languages under study. This bias is independent on the factual mistakes that the model generates, and should also be considered by its users. We provide models to regularly check the bias in text generations for USA, Germany and Spain, as well as in closely related political contexts and languages using a zero-shot approach. As a by-product of our analysis, we created a multilingual corpus of 1.2M newspaper articles with coarse annotations of political stance and topic. We show that distant supervision allows us to build meaningful models for coarse political stance classification as long as the corpus is diverse. We make available this data together with the LMs generations and our code through Zenodo (España-Bonet, 2023) and Github.[12] [12] https://github.com/cristinae/docTransformer This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license. Authors: (1) Cristina España-Bonet, DFKI GmbH, Saarland Informatics Campus. This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license. Authors: Authors: (1) Cristina España-Bonet, DFKI GmbH, Saarland Informatics Campus. Table of Links Abstract and Intro Corpora Compilation Political Stance Classification Summary and Conclusions Limitations and Ethics Statement Acknowledgments and References A. Newspapers in OSCAR 22.01 B. Topics C. Distribution of Topics per Newspaper D. Subjects for the ChatGPT and Bard Article Generation E. Stance Classification at Article Level F. Training Details Abstract and Intro Abstract and Intro Corpora Compilation Corpora Compilation Political Stance Classification Political Stance Classification Summary and Conclusions Summary and Conclusions Limitations and Ethics Statement Limitations and Ethics Statement Acknowledgments and References Acknowledgments and References A. Newspapers in OSCAR 22.01 A. Newspapers in OSCAR 22.01 B. Topics B. Topics C. Distribution of Topics per Newspaper C. Distribution of Topics per Newspaper D. Subjects for the ChatGPT and Bard Article Generation D. Subjects for the ChatGPT and Bard Article Generation E. Stance Classification at Article Level E. Stance Classification at Article Level F. Training Details F. Training Details 4. Summary and Conclusions Media sources have an editorial line and an associated bias. Getting rid of political biases is difficult for humans, but being aware of them helps us getting a global view of news. Biases are sometimes clear and/or appear in form of harmful text, but sometimes are subtle and difficult to detect. These subtle hidden biases are potentially dangerous and lead to manipulation whenever we are not aware of them. In this work, we systematically studied the subtle political biases behind ChatGPT and Bard, those that appear without assigning any persona role (Deshpande et al., 2023). We showed that ChatGPT’s orientation changes with time and it is different across languages. Between Feb and Aug 2023, ChatGPT transitioned from a Left to Neutral political orientation, with a Right-leaning period in the middle for English and Spanish. The evolution for Bard cannot be studied yet. Its current version as of Aug 2023 consistently shows Left-leaning for the 4 languages under study. This bias is independent on the factual mistakes that the model generates, and should also be considered by its users. We provide models to regularly check the bias in text generations for USA, Germany and Spain, as well as in closely related political contexts and languages using a zero-shot approach. As a by-product of our analysis, we created a multilingual corpus of 1.2M newspaper articles with coarse annotations of political stance and topic. We show that distant supervision allows us to build meaningful models for coarse political stance classification as long as the corpus is diverse. We make available this data together with the LMs generations and our code through Zenodo (España-Bonet, 2023) and Github.[12] [12] https://github.com/cristinae/docTransformer

Multilingual Coarse Political Stance Classification of Media: Summary and Conclusions

মিডিয়ার বহুভাষিক মোটা রাজনৈতিক অবস্থানের শ্রেণীবিভাগ: সারাংশ এবং উপসংহার

Mehrsprachige grobe Klassifizierung der politischen Haltung von Medien: Zusammenfassung und Schlussfolgerungen

Clasificación multilingüe de posturas políticas generales de los medios: resumen y conclusiones

Classification multilingue grossière des positions politiques des médias : résumé et conclusions

बहुभाषीय असभ्य राजनीतिक रुख मीडिया का वर्गीकरण: सारांश और निष्कर्ष

多言語メディアの粗い政治的立場の分類：要約と結論

미디어의 다국어 거친 정치적 입장 분류: 요약 및 결론

Classificação Multilíngue da Posição Política Grosseira da Mídia: Resumo e Conclusões

Многоязычная грубая политическая классификация СМИ: Резюме и выводы

Medyanın Çok Dilli Kaba Siyasi Duruş Sınıflandırması: Özet ve Sonuçlar

Phân loại lập trường chính trị thô sơ đa ngôn ngữ của truyền thông: Tóm tắt và kết luận

媒体多语言粗略政治立场分类：总结与结论

Revolutionizing Healthcare: Andy Schoonover's Playbook for Disrupting Entrenched Industries

বিপ্লবী স্বাস্থ্যসেবা: প্রবেশ করা শিল্পগুলিকে ব্যাহত করার জন্য অ্যান্ডি শুনোভারের প্লেবুক

Revolutionierung des Gesundheitswesens: Andy Schoonovers Strategie zur Umwälzung etablierter Branchen

Revolucionando la atención médica: el manual de Andy Schoonover para revolucionar industrias arraigadas

Révolutionner les soins de santé : le manuel d'Andy Schoonover pour perturber les industries bien établies

स्वास्थ्य सेवा में क्रांति: स्थापित उद्योगों में बदलाव के लिए एंडी स्कूनओवर की कार्यपुस्तिका

ヘルスケアの革命: 定着した業界を変革するためのアンディ・シューノーバーの戦略

의료 혁신: 고착화된 산업을 혁신하기 위한 Andy Schoonover의 플레이북

Revolucionando a saúde: o manual de Andy Schoonover para desestabilizar indústrias entrincheiradas

Революция в здравоохранении: книга Энди Шуновера по разрушению устоявшихся отраслей

Sağlık Hizmetinde Devrim Yaratmak: Andy Schoonover'ın Yerleşik Endüstrileri Yıkmaya Yönelik Başucu Kitabı

Cách mạng hóa hoạt động chăm sóc sức khỏe: Sách hướng dẫn cách phá vỡ các ngành công nghiệp cố thủ của Andy Schoonover

医疗保健革命：安迪·斯库诺弗颠覆根深蒂固行业的策略

Characterizing Cable News Bias: Related Research You Should Know About

Next-Gen FHE Toolchains for the Dev Multiverse: How TFHE Is Taking Us There

Are DEXs Finally Become the Bedrock of Crypto Trading?

This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license.
Authors:
(1) Brisha Jain, Independent researcher India and brishajain02@gmail.com;
(2) Mainack Mondal, IIT Kharagpur India and mainack@cse.iitkgp.ac.in. Table of Links Abstract and Intro
Related Work
Data Collection
Analysis Methodology
Results
Limitations
Concluding Discussion
References 5. RESULTS 5.1. Gender bias in interaction frequency and popularity of journalist-politician interactions (RQ1) In order to explore the answer to the first research question, we started with checking if there is a gender bias in the frequency of interaction (i.e., frequency of mentions) between politicians and journalists on Twitter. Male Politicians are more frequently mentioned by journalists: Figure 1a compares the CDF of the number tweets posted by journalists mentioning male and female politicians. We make an interesting observation from this figure. When the receiving politician is male (i.e., in MJ-MP and FJ-MP categories), the number of mentioned tweets (and hence the frequency of journalist-politician interaction) is higher when female politicians are at the receiving end. To that end, a Kruskal-Wallis test among the number of tweets per journalist within the four categories revealed quite statistically significant differences across categories (p << 0.05). Then we performed pairwise Mann-Whitney tests for following up among the four categories (MJ-MP, MJ-FP, FJ-MP, FJ-FP). There is no statistically significant difference when either a Male or Female journalist mentions Male politician accounts. Similarly, there is no statistically significant difference when either a Male or Female journalist mentions a Female politician account. However, there are statistically significant differences in how frequently Male/Female journalists mention Male politicians vs. how frequently they mention Female politicians (all p << 0.05). Next we compare the popularity per tweet directed toward Male vs. Female politicians. vely). Our observation implies that Twitter users in India seem to ascribe greater credibility to the views on male journalists on female politicians compared to the views of female journalists on female politicians. These observations hold for “retweets” as well. Overall, our popularity analysis of these four categories of tweets reveals that while journalists do not suffer from explicit bias in their interactions with politicians, there is evidence to support the existence of gender bias in the amount of interest these interactions generate from active Twitter users. 5.2. Gender bias within the content of journalist-politician tweets (RQ2) In the last section, our analysis showed a significant bias towards the Male politicians from both male and female journalists—the tweets mentioning male politicians are more frequent as well as more popular. However, to that end, we checked if the content of these tweets might be responsible for this bias. Specifically, we checked the emotion and the topic of tweets written by male / female journalists and directed towards male / female politicians. 5.2.1. Emotion analysis. : We used the TweetNLP tool for detecting the emotions of the tweets for each category [6]. TweetNLP provides a diachronic large-language model (TimeLMs) based approach for detecting emotion, specifically from multi-lingual tweets. The goal of this analysis is to determine if there are significant differences in the emotional scores of tweets—if there is that might indicate a gender bias inherently in the tweets based on the gender of sender and receiver. We considered four main emotions: anger, joy, optimism, and sadness and each tweet in each of the four categories were assigned for emotion score along these dimensions. Then we performed a Kruskal-Wallis test to identify if any of the emotions were different across the four categories (MJ-MP, MJ-FP, FJ-MP, FJ-FP). We found that the p-value for each of the four tests (one for each emotion) ranged from 0.16 to 0.99, hinting at no statistically significant difference within the emotions of the tweets. 5.2.2. Topic analysis. : To dig further, we performed a topic analysis of the tweets (using Latent Dirichlet Allocation or LDA) collected across four categories. The goal was to check if the topics of the tweets changed based on the gender of the sender or receiver. As described in Section 4 we identified the optimal number of topics (which are essentially clusters of words) for each category and identified the most significant five words for each topic using the LDA algorithm. For each of the four categories, the optimal number of topics were thirteen. Next, we identified the thirteen topics using the LDA algorithm for each category of tweets and performed a significant word analysis for the detected topics. Specifically, for each category of tweets we selected the topics (e.g., topics from MJ-MP) and picked the significant words representing each topic. Then for each topic we checked if those words also occured in the topics detected from other categories of tweets (if found it will signify that words representing topics are also present in topics detected from other categories of tweets). For each of the four categories of tweets on average 81.5% to 93.8% significant words (representing the topics) occur in topics detected from tweets of other categories. This analysis supports our observation from emotion analysis— the content of tweets across those four categories are the same. However, still the tweets directed towards male politicians attract more interaction compared to the tweets directed towards female politicians. Next we explore a potential reason for this gender bias. 5.3. Potential reason for the gender bias 5.3.1. Inherent Gender Bias in Indian Twitter: We checked a simple statistic regarding top politicians—how many of the most popular politicians (based on the number of Twitter followers) are male vs. they are female. To that end, we leveraged our dataset of top politicians and checked the gender of top 85 politicians (whose Twitter accounts are also part of this study). This analysis uncovered an unsettling gender imbalance among the top politicians—out of 85 top politicians 58 are male and 26 are female. Thus, popular male politicians are almost twice in number compared to popular female politicians. We postulate that this inequality is one of the key reasons behind our observed phenomenon of male politicians attracting significantly more interaction from the general public as well as journalists. In fact, this inequality reflects a systemic bias deeply ingrained in society. This gender disparity extends its influence even to the realm of Twitter, where male politicians tend to garner a larger number of followers than their female counterparts. This phenomenon isn’t isolated; it permeates various sectors, as illustrated by the dominance of men in top positions across industries. In corporate boardrooms, technology firms, and the entertainment sector, leadership roles are predominantly occupied by men. This systematic bias, rooted in societal norms, is further reinforced by the strong correlation between social capital and the attainment of positions of power. Consequently, popularity on Twitter serve as a stark reflection of this intrinsic bias. Addressing these disparities is paramount for fostering gender equality and dismantling deeply entrenched biases in society. This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) Brisha Jain, Independent researcher India and brishajain02@gmail.com; (2) Mainack Mondal, IIT Kharagpur India and mainack@cse.iitkgp.ac.in. This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: Authors: (1) Brisha Jain, Independent researcher India and brishajain02@gmail.com; (2) Mainack Mondal, IIT Kharagpur India and mainack@cse.iitkgp.ac.in. Table of Links Abstract and Intro Related Work Data Collection Analysis Methodology Results Limitations Concluding Discussion References Abstract and Intro Abstract and Intro Related Work Related Work Data Collection Data Collection Analysis Methodology Analysis Methodology Results Results Limitations Limitations Concluding Discussion Concluding Discussion References References 5. RESULTS 5.1. Gender bias in interaction frequency and popularity of journalist-politician interactions (RQ1) In order to explore the answer to the first research question, we started with checking if there is a gender bias in the frequency of interaction (i.e., frequency of mentions) between politicians and journalists on Twitter. Male Politicians are more frequently mentioned by journalists: Figure 1a compares the CDF of the number tweets posted by journalists mentioning male and female politicians. We make an interesting observation from this figure. When the receiving politician is male (i.e., in MJ-MP and FJ-MP categories), the number of mentioned tweets (and hence the frequency of journalist-politician interaction) is higher when female politicians are at the receiving end. To that end, a Kruskal-Wallis test among the number of tweets per journalist within the four categories revealed quite statistically significant differences across categories ( p << 0.05). Then we performed pairwise Mann-Whitney tests for following up among the four categories (MJ-MP, MJ-FP, FJ-MP, FJ-FP). There is no statistically significant difference when either a Male or Female journalist mentions Male politician accounts. Similarly, there is no statistically significant difference when either a Male or Female journalist mentions a Female politician account. However, there are statistically significant differences in how frequently Male/Female journalists mention Male politicians vs. how frequently they mention Female politicians (all p << 0.05). Next we compare the popularity per tweet directed toward Male vs. Female politicians. Male Politicians are more frequently mentioned by journalists: p p vely). Our observation implies that Twitter users in India seem to ascribe greater credibility to the views on male journalists on female politicians compared to the views of female journalists on female politicians. These observations hold for “retweets” as well. Overall, our popularity analysis of these four categories of tweets reveals that while journalists do not suffer from explicit bias in their interactions with politicians, there is evidence to support the existence of gender bias in the amount of interest these interactions generate from active Twitter users. 5.2. Gender bias within the content of journalist-politician tweets (RQ2) In the last section, our analysis showed a significant bias towards the Male politicians from both male and female journalists—the tweets mentioning male politicians are more frequent as well as more popular. However, to that end, we checked if the content of these tweets might be responsible for this bias. Specifically, we checked the emotion and the topic of tweets written by male / female journalists and directed towards male / female politicians. 5.2.1. Emotion analysis. : We used the TweetNLP tool for detecting the emotions of the tweets for each category [6]. TweetNLP provides a diachronic large-language model (TimeLMs) based approach for detecting emotion, specifically from multi-lingual tweets. The goal of this analysis is to determine if there are significant differences in the emotional scores of tweets—if there is that might indicate a gender bias inherently in the tweets based on the gender of sender and receiver. We considered four main emotions: anger, joy, optimism, and sadness and each tweet in each of the four categories were assigned for emotion score along these dimensions. Then we performed a Kruskal-Wallis test to identify if any of the emotions were different across the four categories (MJ-MP, MJ-FP, FJ-MP, FJ-FP). We found that the p -value for each of the four tests (one for each emotion) ranged from 0.16 to 0.99, hinting at no statistically significant difference within the emotions of the tweets. 5.2.1. Emotion analysis. p 5.2.2. Topic analysis. : To dig further, we performed a topic analysis of the tweets (using Latent Dirichlet Allocation or LDA) collected across four categories. The goal was to check if the topics of the tweets changed based on the gender of the sender or receiver. As described in Section 4 we identified the optimal number of topics (which are essentially clusters of words) for each category and identified the most significant five words for each topic using the LDA algorithm. For each of the four categories, the optimal number of topics were thirteen. Next, we identified the thirteen topics using the LDA algorithm for each category of tweets and performed a significant word analysis for the detected topics. Specifically, for each category of tweets we selected the topics (e.g., topics from MJ-MP) and picked the significant words representing each topic. Then for each topic we checked if those words also occured in the topics detected from other categories of tweets (if found it will signify that words representing topics are also present in topics detected from other categories of tweets). For each of the four categories of tweets on average 81.5% to 93.8% significant words (representing the topics) occur in topics detected from tweets of other categories. 5.2.2. Topic analysis. This analysis supports our observation from emotion analysis— the content of tweets across those four categories are the same. However, still the tweets directed towards male politicians attract more interaction compared to the tweets directed towards female politicians. Next we explore a potential reason for this gender bias. 5.3. Potential reason for the gender bias 5.3.1. Inherent Gender Bias in Indian Twitter : We checked a simple statistic regarding top politicians—how many of the most popular politicians (based on the number of Twitter followers) are male vs. they are female. To that end, we leveraged our dataset of top politicians and checked the gender of top 85 politicians (whose Twitter accounts are also part of this study). This analysis uncovered an unsettling gender imbalance among the top politicians—out of 85 top politicians 58 are male and 26 are female. Thus, popular male politicians are almost twice in number compared to popular female politicians. We postulate that this inequality is one of the key reasons behind our observed phenomenon of male politicians attracting significantly more interaction from the general public as well as journalists. 5.3.1. Inherent Gender Bias in Indian Twitter In fact, this inequality reflects a systemic bias deeply ingrained in society. This gender disparity extends its influence even to the realm of Twitter, where male politicians tend to garner a larger number of followers than their female counterparts. This phenomenon isn’t isolated; it permeates various sectors, as illustrated by the dominance of men in top positions across industries. In corporate boardrooms, technology firms, and the entertainment sector, leadership roles are predominantly occupied by men. This systematic bias, rooted in societal norms, is further reinforced by the strong correlation between social capital and the attainment of positions of power. Consequently, popularity on Twitter serve as a stark reflection of this intrinsic bias. Addressing these disparities is paramount for fostering gender equality and dismantling deeply entrenched biases in society.

Uncovering Gender Bias within Journalist-Politician Interaction in Indian Twitter: Results

ভারতীয় টুইটারে সাংবাদিক-রাজনীতিবিদ ইন্টারঅ্যাকশনের মধ্যে লিঙ্গ পক্ষপাত উন্মোচন: ফলাফল

Aufdeckung geschlechtsspezifischer Voreingenommenheit in der Interaktion zwischen Journalisten und Politikern auf Twitter in Indien: Ergebnisse

Descubriendo el sesgo de género en la interacción entre periodistas y políticos en Twitter indio: resultados

Découvrir les préjugés sexistes dans les interactions journalistes-hommes politiques sur Twitter indien : résultats

भारतीय ट्विटर पर पत्रकार-राजनेता बातचीत में लैंगिक पूर्वाग्रह का खुलासा: परिणाम

インドのツイッターにおけるジャーナリストと政治家のやり取りにおけるジェンダーバイアスの解明：結果

인도 트위터의 언론인-정치인 상호 작용에서 성 편견 발견: 결과

Descobrindo o preconceito de gênero na interação jornalista-político no Twitter indiano: resultados

Выявление гендерных предубеждений во взаимодействии журналистов и политиков в индийском Твиттере: результаты

Hint Twitter'ında Gazeteci-Politikacı Etkileşimindeki Cinsiyet Önyargısını Ortaya Çıkarmak: Sonuçlar

Khám phá thành kiến giới tính trong tương tác giữa nhà báo và chính trị gia trên Twitter của Ấn Độ: Kết quả

揭示印度推特上记者与政客互动中的性别偏见：结果

Uncovering Gender Bias within Journalist-Politician Interaction in Indian Twitter: Abstract & Intro

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Découvrir les préjugés sexistes dans les interactions journalistes-hommes politiques sur Twitter indien : résumé et introduction

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揭示印度推特上记者与政客互动中的性别偏见：摘要与简介

Advancing net worth is as easy as a click. Democratized online trading platforms have expanded portfolios while increasing the chances of cybersecurity breaches. These websites are more popular and accessible than ever — and threat actors know this. Techies and investors with accounts on these sites must acknowledge the threat landscape. Hackers grow their skills and creativity daily, so cyber hygiene equates to financial stability. Overview of Cybersecurity Risks in Online Trading Moderators, administrators, and users alike must remain alert for signs of security compromises. Their frequency dictates the reputation of all trading platforms, reducing trust in investors. What are the most prominent cyberattack variants on online trading sites? Server Misconfigurations Most online traders are in service thanks to third-party cloud providers. External hosts own data centers, which are equally vulnerable to cyberattacks if unprotected. While outsourcing provides boons, trusting public vendors to maintain security standards is tricky. One recent incident occurred on the Forex trading site, FBS. One server was left without encryption or passwords, leaving 20 terabytes of data open for the taking. Hackers may not need advanced techniques to compromise billions of users' information. They merely need to look around for negligent trading companies. Social Engineering and Insider Threats This is one of the most stealthy cyber intrusions because cybercriminals manipulate real people instead of digital assets. Brokers inside the firm may work alongside criminal outfits and be bribed or blackmailed into helping them. Alternatively, the insider threat may have been a double agent from the beginning of their employment. It gives immediate ingress behind cyber defenses that are hard to catch. This allows those under the influence of social engineering to manipulate the market or commit fraud from within. Phishing It is common for hackers to resemble trusted sources, such as emails or websites. Transferring funds from a trading account is as simple as investors handing over the information. Spear phishing is prevalent in high-profile environments. This tactic targets specific individuals or small groups. It could coincide with whaling, which jeopardizes individuals with high net worth or a lot to lose. People who don’t develop a risk management plan for their portfolio may feel the brunt of spear phishing more than others. Malware and Ransomware Threat actors will stop at nothing to take over trading software, records, servers, and systems. They do this with malware and ransomware because hackers know the people they are attacking have the funds on hand. The likelihood that criminals will receive payment for stolen information is high in fintech. Impulsive, emotional investing is already a risk for online trading volatility, and this phenomenon is worse with cyberthreats. Vulnerabilities in Online Trading Platforms Online trading organizations suffer from cyberattacks because of security oversights. Users and staff must recognize these solutions to the most notable red flags. The repercussions are drained funds and stolen identities, to name a few. Inadequate Authentication Measures These sites may not have as comprehensive verification as they could. This goes past login strategies, such as two-factor authentication or using biometrics. Authentication measures must occur while traders explore the platform. Is it set up to identify unusual account access attempts or allow transactions and communications to occur without encryption? Poor Compliance Adherence Many websites do not follow agency best practices. They need to adhere to cybersecurity frameworks, among others. This includes data protection policies and anti-money laundering legislation, and trading platforms must practice due diligence to prevent it. Spontaneous withdrawals of specific varieties should not be allowed in a secure program. Insecure APIs If communication between multiple components in online trading software is insecure, then the rest of the platform is, too. Compliance expert OWASP provides many suggestions for protecting APIs, such as reviewing unrestricted resource consumption or server-side request forgery. Best Practices for Securing Online Trading Accounts Everyone involved in online trading must adopt industry-leading habits to lessen attack severity. Easy-to-implement suggestions include: Establishing two- or multifactor authentication with text, email, and biometric options
Using strong password guidelines
Automating updates for trading software to the most recent versions
Securing internet connections and servers
Updating firewalls
Setting up alerts for suspected malicious activity
Getting to know a reputable broker
Writing a cybersecurity incident response plan However, the most beneficial way to secure websites is to educate and motivate employees for these trading sites. Disengagement and alert fatigue are rampant in cybersecurity circles. It makes most breaches a result of human error instead of a system fault. Regulatory Frameworks and Compliance Standards Protecting Traders Regulatory agencies work tirelessly to update and innovate on existing security standards. Fintech is vulnerable, so it requires special attention. Organizations and laws overseeing financial services and preventing brokerage fraud concerns include: U.S. Securities and Exchange Commission (SEC)
Securities Investor Protection Corporation (SIPC)
Financial Industry Regulatory Authority (FINRA)
General Data Protection Regulation (GDPR)
Payment Card Industry Data Security Standard (PCI DSS)
International Organization for Standardization (ISO) 27001
Open Worldwide Application Security Project (OWASP)
Hypertext Transfer Protocol Secure (HTTPS) The implications of noncompliance are severe for sites and traders, yet many are underperforming. Few requirements for transparency exist, and despite guidelines, not every platform is overseen by authorities. Emerging Technologies for Enhancing Online Trading Security Several strategies cybersecurity analysts employ to fight hackers have become antiquated. Advanced technologies are necessary to adapt to sneaky revolutions in the hacking world. Blockchain is one of the most competitive options for increasing defenses. Its use of hashes and ledgers makes it one of digital spaces' most substantial verification measures. Tracking transactions has never been more transparent and certifiable. Blockchain is not a perfect technology, but enhancements are developing it into the cybersecurity behemoth the industry is begging for. AI-driven solutions have the most growth potential. The technology still needs refining, but it could be the most versatile and effective at stopping cybercriminals from entering online trading sites. It would use machine and deep learning to understand the most prominent risk variants on the site.  Designing isolation and remediation tactics with minimal human intervention would make it more proficient. Wiser Online Trading to Beat Hackers Breaches in any industry could be destructive, but online trading platforms have access to countless dollars and data points. They are enticing targets for experienced cybercriminals. Enforcing strict cybersecurity regulations is vital, regardless of upfront investments and complexity. Fintech cannot afford the losses, and neither can its customers. Private and governmental collaboration is necessary to combat threats in digital landscapes. Advancing net worth is as easy as a click . Democratized online trading platforms have expanded portfolios while increasing the chances of cybersecurity breaches. These websites are more popular and accessible than ever — and threat actors know this. Advancing net worth is as easy as a click Techies and investors with accounts on these sites must acknowledge the threat landscape. Hackers grow their skills and creativity daily, so cyber hygiene equates to financial stability. Overview of Cybersecurity Risks in Online Trading Moderators, administrators, and users alike must remain alert for signs of security compromises. Their frequency dictates the reputation of all trading platforms, reducing trust in investors. What are the most prominent cyberattack variants on online trading sites? Server Misconfigurations Most online traders are in service thanks to third-party cloud providers. External hosts own data centers, which are equally vulnerable to cyberattacks if unprotected. While outsourcing provides boons, trusting public vendors to maintain security standards is tricky. One recent incident occurred on the Forex trading site, FBS. One server was left without encryption or passwords, leaving 20 terabytes of data open for the taking. Hackers may not need advanced techniques to compromise billions of users' information. They merely need to look around for negligent trading companies. 20 terabytes of data open 20 terabytes of data open Social Engineering and Insider Threats This is one of the most stealthy cyber intrusions because cybercriminals manipulate real people instead of digital assets. Brokers inside the firm may work alongside criminal outfits and be bribed or blackmailed into helping them. Alternatively, the insider threat may have been a double agent from the beginning of their employment. It gives immediate ingress behind cyber defenses that are hard to catch. This allows those under the influence of social engineering to manipulate the market or commit fraud from within. immediate ingress behind cyber defenses immediate ingress behind cyber defenses Phishing It is common for hackers to resemble trusted sources, such as emails or websites. Transferring funds from a trading account is as simple as investors handing over the information. Spear phishing is prevalent in high-profile environments. This tactic targets specific individuals or small groups. It could coincide with whaling, which jeopardizes individuals with high net worth or a lot to lose. People who don’t develop a risk management plan for their portfolio may feel the brunt of spear phishing more than others. develop a risk management plan develop a risk management plan Malware and Ransomware Threat actors will stop at nothing to take over trading software, records, servers, and systems. They do this with malware and ransomware because hackers know the people they are attacking have the funds on hand. The likelihood that criminals will receive payment for stolen information is high in fintech. Impulsive, emotional investing is already a risk for online trading volatility, and this phenomenon is worse with cyberthreats. Vulnerabilities in Online Trading Platforms Online trading organizations suffer from cyberattacks because of security oversights. Users and staff must recognize these solutions to the most notable red flags. The repercussions are drained funds and stolen identities, to name a few. Inadequate Authentication Measures These sites may not have as comprehensive verification as they could. This goes past login strategies, such as two-factor authentication or using biometrics. Authentication measures must occur while traders explore the platform. Is it set up to identify unusual account access attempts or allow transactions and communications to occur without encryption? Poor Compliance Adherence Many websites do not follow agency best practices. They need to adhere to cybersecurity frameworks, among others. This includes data protection policies and anti-money laundering legislation, and trading platforms must practice due diligence to prevent it. Spontaneous withdrawals of specific varieties should not be allowed in a secure program. Insecure APIs If communication between multiple components in online trading software is insecure, then the rest of the platform is, too. Compliance expert OWASP provides many suggestions for protecting APIs, such as reviewing unrestricted resource consumption or server-side request forgery. reviewing unrestricted resource consumption reviewing unrestricted resource consumption Best Practices for Securing Online Trading Accounts Everyone involved in online trading must adopt industry-leading habits to lessen attack severity. Easy-to-implement suggestions include: Establishing two- or multifactor authentication with text, email, and biometric options Using strong password guidelines Automating updates for trading software to the most recent versions Securing internet connections and servers Updating firewalls Setting up alerts for suspected malicious activity Getting to know a reputable broker Writing a cybersecurity incident response plan Establishing two- or multifactor authentication with text, email, and biometric options Using strong password guidelines Automating updates for trading software to the most recent versions Securing internet connections and servers Updating firewalls Setting up alerts for suspected malicious activity Getting to know a reputable broker Writing a cybersecurity incident response plan However, the most beneficial way to secure websites is to educate and motivate employees for these trading sites. Disengagement and alert fatigue are rampant in cybersecurity circles. It makes most breaches a result of human error instead of a system fault. Regulatory Frameworks and Compliance Standards Protecting Traders Regulatory agencies work tirelessly to update and innovate on existing security standards. Fintech is vulnerable, so it requires special attention. Organizations and laws overseeing financial services and preventing brokerage fraud concerns include: preventing brokerage fraud concerns preventing brokerage fraud concerns U.S. Securities and Exchange Commission (SEC) Securities Investor Protection Corporation (SIPC) Financial Industry Regulatory Authority (FINRA) General Data Protection Regulation (GDPR) Payment Card Industry Data Security Standard (PCI DSS) International Organization for Standardization (ISO) 27001 Open Worldwide Application Security Project (OWASP) Hypertext Transfer Protocol Secure (HTTPS) U.S. Securities and Exchange Commission (SEC) Securities Investor Protection Corporation (SIPC) Financial Industry Regulatory Authority (FINRA) General Data Protection Regulation (GDPR) Payment Card Industry Data Security Standard (PCI DSS) International Organization for Standardization (ISO) 27001 Open Worldwide Application Security Project (OWASP) Hypertext Transfer Protocol Secure (HTTPS) The implications of noncompliance are severe for sites and traders, yet many are underperforming. Few requirements for transparency exist, and despite guidelines, not every platform is overseen by authorities. Emerging Technologies for Enhancing Online Trading Security Several strategies cybersecurity analysts employ to fight hackers have become antiquated. Advanced technologies are necessary to adapt to sneaky revolutions in the hacking world. are necessary to adapt are necessary to adapt Blockchain is one of the most competitive options for increasing defenses. Its use of hashes and ledgers makes it one of digital spaces' most substantial verification measures. Tracking transactions has never been more transparent and certifiable. Blockchain is not a perfect technology, but enhancements are developing it into the cybersecurity behemoth the industry is begging for. AI-driven solutions have the most growth potential. The technology still needs refining, but it could be the most versatile and effective at stopping cybercriminals from entering online trading sites. It would use machine and deep learning to understand the most prominent risk variants on the site.  Designing isolation and remediation tactics with minimal human intervention would make it more proficient. Wiser Online Trading to Beat Hackers Breaches in any industry could be destructive, but online trading platforms have access to countless dollars and data points. They are enticing targets for experienced cybercriminals. Enforcing strict cybersecurity regulations is vital, regardless of upfront investments and complexity. Fintech cannot afford the losses, and neither can its customers. Private and governmental collaboration is necessary to combat threats in digital landscapes.

Cybersecurity Risks Worth Considering in Online Trading

অনলাইন ট্রেডিংয়ে সাইবার নিরাপত্তার ঝুঁকি বিবেচনা করা উচিত

Cybersicherheitsrisiken, die beim Online-Handel zu berücksichtigen sind

Riesgos de ciberseguridad que vale la pena considerar en el comercio en línea

Risques de cybersécurité à prendre en compte dans le trading en ligne

ऑनलाइन ट्रेडिंग में साइबर सुरक्षा जोखिम पर विचार करना उचित है

オンライン取引で考慮すべきサイバーセキュリティリスク

온라인 거래에서 고려해야 할 사이버 보안 위험

Riscos de segurança cibernética que valem a pena considerar no comércio online

Риски кибербезопасности, которые стоит учитывать при онлайн-торговле

Çevrimiçi Ticarette Dikkate Alınması Gereken Siber Güvenlik Riskleri

Rủi ro an ninh mạng đáng xem xét trong giao dịch trực tuyến

在线交易中值得考虑的网络安全风险

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