Why is the #HaryanaElectionResult trending on Twitter?

Twitter is gone anyway, its public APIs have shut down

tweets

AI and Gender Equality on Twitter

Look at these guys. One works 16 hours a day. One works 4 hours a week. 2 billionaires. 1 mind-blowing lesson about success: (I can't believe no one has connected the dots)

Thread of cool maps you've (probably) never seen before 1. All roads lead to Rome

Heiress to one of the world’s most powerful families. Her grandfather cut her out of the $15.4 BILLION family fortune after her scandal. But she fooled the world with her “dumb blond” persona and built a $300 MILLION business portfolio. This is the crazy story of Paris Hilton:

daniel waldman@the_waldman@bleacherreport. go bearsSan Francisco, CAbr.app.link/Get-the-BR-appJoined September 2013665 Following505 Followers

Bassam Haddad@4BassamFounding Director of MidEast & Islamic Studies Program, George Mason University, Executive Director of http://ArabStudiesInstitute.org. Satire warning!jadaliyya.comJoined April 2009

Maura Finkelstein@Dr_maurafWriter. Ethnographer. Professor. Author of The Archive of Loss: Lively Ruination in Mill Land Mumbai (Duke UP 2019) rep’d by @a_la_ash she/her/Free Palestine Philadelphia, PAmaurafinkelstein.comJoined February 2017

Alex Sarabia@SarabiaTXCommunications Director for @SenWarren Previously @JoaquinCastrotx @JulianCastro #GoSpursGo he/him/él

Scholars have taken keen advantage of these social media norms.

From a branding perspective, it’s a bizarre and self-sabotaging move. Twitter is an established, internationally recognizable name. It’s cited in untold numbers of books, broadcasts, TV shows and news articles. Every internet-literate person knows what a tweet is. Needless to say, it will be hard to persuade regular people to refer to X as “X” instead of good ol’ Twitter. Plus, a single letter is difficult to google. These are just some of the many, many reasons why Twitter/X users are dunking on Musk’s new rebrand.

Venkatesh Rao thinks that the Nazi bar analogy is “an example of a bad metaphor contagion effect” and points to a 2010 post of his about warren vs plaza architectures. He believes that Twitter, for example, is a plaza, whereas Substack is a warren: A warren is a social environment where no participant can see beyond their little corner of a larger maze. Warrens emerge through people personalizing and customizing their individual environments with some degree of emergent collaboration. A plaza is an environment where you can easily get to a global/big picture view of the whole thing. Plazas are created by central planners who believe they know what’s best for everyone.

La obra de Don Pablo González Casanova todavía está por descubrirse...

Wikipedia is inherently hierarchical and therefore subject to the biases of higher ranking editors, independent of their merits.

Perhaps it’s not a force for good at all. Alex Shephard @alex_shephard

It’s likely that some facsimile of Twitter will exist, far into the future. But a seismic shift in how the platform is perceived has occurred. If it isn’t good for breaking news, then what good is it? Perhaps it’s not a force for good at all.

One of the things I loved most about Twitter was the way it could throw things in front of me that I never would have even thought to go look for on my own.

dishes at restaurants so their kids

A script searches Twitter for "X is my new favorite word" and adds it to this list.

In Notes, writers will be able to post short-form content and share ideas with each other and their readers. Like our Recommendations feature, Notes is designed to drive discovery across Substack. But while Recommendations lets writers promote publications, Notes will give them the ability to recommend almost anything—including posts, quotes, comments, images, and links.

Twitter banning him for saying women should "bear responsibility" for being sexually assaulted. He has since been reinstated.

TheSateliteCombinationCard IndexCabinetandTelephoneStand

Mastodon Brought a Protocol to a Product Fight

We found that while some participants were aware of bots’ primary characteristics, others provided abstract descriptions or confused bots with other phenomena. Participants also struggled to classify accounts correctly (e.g., misclassifying > 50% of accounts) and were more likely to misclassify bots than non-bots. Furthermore, we observed that perceptions of bots had a significant effect on participants’ classification accuracy. For example, participants with abstract perceptions of bots were more likely to misclassify. Informed by our findings, we discuss directions for developing user-centered interventions against bots.

We analyzed URLs cited in Twitter messages before and after the temporary interruption of the vaccine development on September 9, 2020 to investigate the presence of low credibility and malicious information. We show that the halt of the AstraZeneca clinical trials prompted tweets that cast doubt, fear and vaccine opposition. We discovered a strong presence of URLs from low credibility or malicious websites, as classified by independent fact-checking organizations or identified by web hosting infrastructure features. Moreover, we identified what appears to be coordinated operations to artificially promote some of these URLs hosted on malicious websites.

When public health emergencies break out, social bots are often seen as the disseminator of misleading information and the instigator of public sentiment (Broniatowski et al., 2018; Shi et al., 2020). Given this research status, this study attempts to explore how social bots influence information diffusion and emotional contagion in social networks.

. Furthermore, our results add to the growing body of literature documenting—at least at this historical moment—the link between extreme right-wing ideology and misinformation8,14,24 (although, of course, factors other than ideology are also associated with misinformation sharing, such as polarization25 and inattention17,37).

And finally, at the individual level, we found that estimated ideological extremity was more strongly associated with following elites who made more false or inaccurate statements among users estimated to be conservatives compared to users estimated to be liberals. These results on political asymmetries are aligned with prior work on news-based misinformation sharing

We found that users who followed elites who made more false or inaccurate statements themselves shared news from lower-quality news outlets (as judged by both fact-checkers and politically-balanced crowds of laypeople), used more toxic language, and expressed more moral outrage.

Aligned with prior work finding that people who identify as conservative consume15, believe24, and share more misinformation8,14,25, we also found a positive correlation between users’ misinformation-exposure scores and the extent to which they are estimated to be conservative ideologically (Fig. 2c; b = 0.747, 95% CI = [0.727,0.767] SE = 0.010, t (4332) = 73.855, p < 0.001), such that users estimated to be more conservative are more likely to follow the Twitter accounts of elites with higher fact-checking falsity scores. Critically, the relationship between misinformation-exposure score and quality of content shared is robust controlling for estimated ideology

Interestingly, the fraction of low-credible URLs coming from U.S. dropped from 74% in the vax devel-opment period to 55% in the vax rollout. This large decrease can be directly ascribed to Twitter’s moderationpolicy: 46% of cross-border retweets of U.S. users linking to low-credible websites in the vax developmentperiod came from accounts that have been suspended following the U.S. Capitol attack (see Figure 8 (a), Ap-pendix).

We find that, during the pandemic, no-vax communities became more central in the country-specificdebates and their cross-border connections strengthened, revealing a global Twitter anti-vaccinationnetwork. U.S. users are central in this network, while Russian users also become net exporters ofmisinformation during vaccination roll-out. Interestingly, we find that Twitter’s content moderationefforts, and in particular the suspension of users following the January 6th U.S. Capitol attack, had aworldwide impact in reducing misinformation spread about vaccines. These findings may help publichealth institutions and social media platforms to mitigate the spread of health-related, low-credibleinformation by revealing vulnerable online communities

We estimated the contribution of veri-fied accounts to sharing and amplifying links to Russian propagandaand low-credibility sources, noticing that they have a dispropor-tionate role. In particular, superspreaders of Russian propagandaare mostly accounts verified by both Facebook and Twitter, likelydue to Russian state-run outlets having associated accounts withverified status. In the case of generic low-credibility sources, a sim-ilar result applies to Facebook but not to Twitter, where we alsonotice a few superspreaders accounts that are not verified by theplatform.

On Twitter, the picture is very similar in the case of Russianpropaganda, where all accounts are verified (with a few exceptions)and mostly associated with news outlets, and generate over 68%of all retweets linking to these websites (see panel a of Figure 4).For what concerns low-credibility news, there are both verified (wecan notice the presence of seanhannity) and not verified users,and only a few of them are directly associated with websites (e.g.zerohedge or Breaking911). Here the top 15 accounts generateroughly 30% of all retweets linking to low-credibility websites.

Figure 5: Top 15 spreaders of Russian propaganda (a) andlow-credibility content (b) ranked by the proportion ofretweets generated over the period of observation, with re-spect to all retweets linking to websites in each group. Weindicate those that are not verified using “hatched” bars

Figure 4: Top 15 spreaders of Russian propaganda (a) andlow-credibility content (b) ranked by the proportion of in-teractions generated over the period of observation, withrespect to all interactions around links to websites in eachgroup. Given the large number of verified accounts, we indi-cate those not verified using “hatched” bars.

we found that social bots played a bridge role in diffusion in the apparent directional topic like “Wuhan Lab”. Previous research also found that social bots play some intermediary roles between elites and everyday users regarding information flow [43]. In addition, verified Twitter accounts continue to be very influential and receive more retweets, whereas social bots retweet more tweets from other users. Studies have found that verified media accounts remain more central to disseminating information during controversial political events [75]. However, occasionally, even the verified accounts—including those of well-known public figures and elected officials—sent misleading tweets. This inspired us to investigate the validity of tweets from verified accounts in subsequent research. It is also essential to rely solely on science and evidence-based conclusions and avoid opinion-based narratives in a time of geopolitical conflict marked by hidden agendas, disinformation, and manipulation [76].

In Figure 6, the node represented by human A is a high-degree centrality account with poor discrimination ability for disinformation and rumors; it is easily affected by misinformation retweeted by social bots. At the same time, it will also refer to the opinions of other persuasive folk opinion leaders in the retweeting process. Human B represents the official institutional account, which has a high in-degree and often pushes the latest news, preventive measures, and suggestions related to COVID-19. Human C represents a human account with high media literacy, which mainly retweets information from information sources with high credibility. It has a solid ability to identify information quality and is not susceptible to the proliferation of social bots. Human D actively creates and spreads rumors and conspiracy theories and only retweets unverified messages that support his views in an attempt to expand the influence. Social bots K, M, and N also spread unverified information (rumors, conspiracy theories, and disinformation) in the communication network without fact-checking. Social bot L may be a social bot of an official agency.

We analyzed and visualized Twitter data during the prevalence of the Wuhan lab leak theory and discovered that 29% of the accounts participating in the discussion were social bots. We found evidence that social bots play an essential mediating role in communication networks. Although human accounts have a more direct influence on the information diffusion network, social bots have a more indirect influence. Unverified social bot accounts retweet more, and through multiple levels of diffusion, humans are vulnerable to messages manipulated by bots, driving the spread of unverified messages across social media. These findings show that limiting the use of social bots might be an effective method to minimize the spread of conspiracy theories and hate speech online.

deleted its controversial new policy

@TwitterSupport

In advance of deleting my Twitter account, I made this web page that lets you search my tweets, link to an archived version, and read whole threads I wrote.https://tinysubversions.com/twitter-archive/I will eventually release this as a website I host where you drop your Twitter zip archive in and it spits out the 100% static site you see here. Then you can just upload it somewhere and you have an archive that is also easy to style how you like it.

Twitter has, like its fellow social media platforms, been working for years to make the process of moderation efficient and systematic enough to function at scale. Not just so the platform isn’t overrun with bots and spam, but in order to comply with legal frameworks like FTC orders and the GDPR.

The trolling is paramount. When former Facebook CSO and Stanford Internet Observatory leader Alex Stamos asked whether Musk would consider implementing his detailed plan for “a trustworthy, neutral platform for political conversations around the world,” Musk responded, “You operate a propaganda platform.” Musk doesn’t appear to want to substantively engage on policy issues: He wants to be aggrieved.

Twitter has never been able to deal with the fact its users both hate using it and also hate each other.

The most typical way users encounter trending content is when a massively viral tweet — or subtweets about that tweet or the discourse it created — enters their feed. Then it’s up to them to figure out what kind of account posted the tweet, what kind of accounts are sharing the tweet, and what accounts are saying about the tweet.

my best guess is it’s the moderation

The presence of Twitter’s code — known as the Twitter advertising pixel — has grown more troublesome since Elon Musk purchased the platform.AdvertisementThat’s because under the terms of Musk’s purchase, large foreign investors were granted special privileges. Anyone who invested $250 million or more is entitled to receive information beyond what lower-level investors can receive. Among the higher-end investors include a Saudi prince’s holding company and a Qatari fund.

Last night I posted a message to both Mastodon and Twitter saying how great M's support for RSS is. Apparently a lot of people on Masto didn't know about it and the response has been resounding. And the numbers are very lopsided. The piece has been "boosted" (the Masto equiv of RT) 1.1K times, yet I only have 3.7K followers there. Meanwhile on Twitter, where I have 69K followers, it has been RTd just 17 times. My feeling was previously that Mastodon was more alive, it's good to have a number to put behind that.

The real question isn’t whether platforms like Twitter and Facebook are public squares (because they aren’t), but whether they should be. Should everyone have a right to access these platforms and speak through them the way we all have a right to stand on a soap box downtown and speak through a megaphone? It’s a more complicated ask than we realize—certainly more complicated than those (including Elon Musk himself) who seem to think merely declaring Twitter a public square is sufficient.

This tweet, along with the reinstatement of Donald Trump’s Twitter account, has caused a whirlwind of discussion and debate on the platform—the same arguments about free speech and social media as the “digital public square” that seem to go nowhere, regardless of how often we try. And part of the reason they go nowhere is because the situation is both more simple and more complicated than many of us want to recognize.

What I missed about Mastodon was its very different culture. Ad-driven social media platforms are willing to tolerate monumental volumes of abusive users. They’ve discovered the same thing the Mainstream Media did: negative emotions grip people’s attention harder than positive ones. Hate and fear drives engagement, and engagement drives ad impressions. Mastodon is not an ad-driven platform. There is absolutely zero incentives to let awful people run amok in the name of engagement. The goal of Mastodon is to build a friendly collection of communities, not an attention leeching hate mill. As a result, most Mastodon instance operators have come to a consensus that hate speech shouldn’t be allowed. Already, that sets it far apart from twitter, but wait, there’s more. When it comes to other topics, what is and isn’t allowed is on an instance-by-instance basis, so you can choose your own adventure.

The TTRG (time to reply guy) was getting so fast, that I can’t actually remember the last time I tweeted something helpful like a design or development tip. I just couldn’t be arsed, knowing some dickhead would be around to waste my time with whataboutisms and “will it scale”?

The Post analyzed data from ProPublica’s Represent tool, which tracks congressional Twitter activity.

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