<?xml version="1.0" encoding="UTF-8"?>
 <rdf:RDF xmlns="http://purl.org/rss/1.0/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:cc="http://web.resource.org/cc/" xmlns:syn="http://purl.org/rss/1.0/modules/syndication/" xmlns:admin="http://webns.net/mvcb/">
  <channel rdf:about="http://pinboard.in">
    <title>Pinboard (cshalizi)</title>
    <link>https://pinboard.in/u:cshalizi/public/</link>
    <description>recent bookmarks from cshalizi</description>
    <items>
      <rdf:Seq>	<rdf:li rdf:resource="https://github.com/igorbrigadir/awesome-twitter-algo"/>
	<rdf:li rdf:resource="https://www.nytimes.com/2023/04/18/magazine/twitter-dying.html"/>
	<rdf:li rdf:resource="https://oxford.universitypressscholarship.com/view/10.1093/oso/9780197582268.001.0001/oso-9780197582268?rskey=PzGaKz&amp;result=254"/>
	<rdf:li rdf:resource="https://ravenmagazine.org/magazine/twitter-the-intimacy-machine/"/>
	<rdf:li rdf:resource="https://medium.com/@fondalee/twitter-is-the-worst-reader-2ac343c41874"/>
	<rdf:li rdf:resource="https://www.washingtonpost.com/outlook/2021/10/27/twitter-amplifies-conservative-politicians/"/>
	<rdf:li rdf:resource="https://www.newyorker.com/news/essay/on-the-internet-were-always-famous"/>
	<rdf:li rdf:resource="https://endofsafety.substack.com/p/on-those-who-hate-twitter-but-cannot"/>
	<rdf:li rdf:resource="https://arxiv.org/abs/2104.13259"/>
	<rdf:li rdf:resource="https://arxiv.org/abs/2104.07175"/>
	<rdf:li rdf:resource="https://arxiv.org/abs/2006.09938"/>
	<rdf:li rdf:resource="https://arxiv.org/abs/2003.03667"/>
	<rdf:li rdf:resource="https://catalyst-journal.com/vol4/no2/the-poisoned-chalice-of-hashtag-activism"/>
	<rdf:li rdf:resource="https://www.bbc.com/worklife/article/20200123-how-your-twitter-feed-could-help-find-your-dream-job"/>
	<rdf:li rdf:resource="http://nautil.us/blog/scientists-can-predict-your-job-by-your-social_media-personality"/>
	<rdf:li rdf:resource="https://www.pnas.org/content/116/52/26459"/>
	<rdf:li rdf:resource="http://www.theonion.com/article/twitter-introduces-red-x-mark-verify-users-its-oka-56527"/>
	<rdf:li rdf:resource="http://krugman.blogs.nytimes.com/2012/02/08/the-power-law-of-twitter/"/>
	<rdf:li rdf:resource="http://arxiv.org/abs/1110.0535"/>
	<rdf:li rdf:resource="http://arxiv.org/abs/1107.4009"/>
      </rdf:Seq>
    </items>
  </channel><item rdf:about="https://github.com/igorbrigadir/awesome-twitter-algo">
    <title>GitHub - igorbrigadir/awesome-twitter-algo: The release of the Twitter algorithm, annotated for recsys</title>
    <dc:date>2023-05-02T20:39:10+00:00</dc:date>
    <link>https://github.com/igorbrigadir/awesome-twitter-algo</link>
    <dc:creator>cshalizi</dc:creator><dc:subject>twitter recommender_systems to_teach:data-mining have_read</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:661b081ee535/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:twitter"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:recommender_systems"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to_teach:data-mining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:have_read"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.nytimes.com/2023/04/18/magazine/twitter-dying.html">
    <title>What Was Twitter, Anyway? - The New York Times</title>
    <dc:date>2023-05-02T19:28:13+00:00</dc:date>
    <link>https://www.nytimes.com/2023/04/18/magazine/twitter-dying.html</link>
    <dc:creator>cshalizi</dc:creator><dc:subject>twitter social_media networked_life have_read re:actually-dr-internet-is-the-name-of-the-monsters-creator</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:e52ebec490a6/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:twitter"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:social_media"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:networked_life"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:have_read"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:re:actually-dr-internet-is-the-name-of-the-monsters-creator"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://oxford.universitypressscholarship.com/view/10.1093/oso/9780197582268.001.0001/oso-9780197582268?rskey=PzGaKz&amp;result=254">
    <title>Tweeting is Leading: How Senators Communicate and Represent in the Age of Twitter - Oxford Scholarship</title>
    <dc:date>2022-07-03T13:50:51+00:00</dc:date>
    <link>https://oxford.universitypressscholarship.com/view/10.1093/oso/9780197582268.001.0001/oso-9780197582268?rskey=PzGaKz&amp;result=254</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["Social media is changing the business of representation and lawmaker reputation building, and this book uses the US Senate to illustrate the constituent-driven nature of political communication. I offer a critical analysis of senators’ communication on Twitter, the forces that shape it, and the agendas that result. Senators strategically communicate a political image that reflects their unique political persona. They have to decide what they want to be known for, crafting communications that prioritize legislation, constituent service, and party politics in ways that meet the interests of their constituencies and foster promising electoral returns. Senators’ communicated, public priorities—what is termed in this book as the rhetorical agenda—offer a necessary tool for understanding how senators link their carefully crafted public image with potential voters. The rhetorical agenda uses more than 180,000 lawmaker tweets to challenge what we know about representation, removing the institutional and political constraints on congressional communication and giving lawmakers a messaging platform where individual discretion is high, the relative costs are low, and someone is always watching."

--- Last two tags reflect my evaluation and not the author's...]]></description>
<dc:subject>books:noted rhetorical_self-fashioning text_mining social_media networked_life twitter congress us_politics political_science our_decrepit_institutions re:actually-dr-internet-is-the-name-of-the-monsters-creator in_NB</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:f307ec0f3631/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:books:noted"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:rhetorical_self-fashioning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:text_mining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:social_media"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:networked_life"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:twitter"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:congress"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:us_politics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:political_science"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:our_decrepit_institutions"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:re:actually-dr-internet-is-the-name-of-the-monsters-creator"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:in_NB"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://ravenmagazine.org/magazine/twitter-the-intimacy-machine/">
    <title>Twitter, the Intimacy Machine - The Raven Magazine</title>
    <dc:date>2021-12-19T06:09:19+00:00</dc:date>
    <link>https://ravenmagazine.org/magazine/twitter-the-intimacy-machine/</link>
    <dc:creator>cshalizi</dc:creator><dc:subject>social_media twitter re:actually-dr-internet-is-the-name-of-the-monsters-creator via:henry_farrell to:blog</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:68f0541a232a/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:social_media"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:twitter"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:re:actually-dr-internet-is-the-name-of-the-monsters-creator"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:via:henry_farrell"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:blog"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://medium.com/@fondalee/twitter-is-the-worst-reader-2ac343c41874">
    <title>Twitter Is The Worst Reader. I’ve been in my share of Twitter… | by Fonda Lee | Nov, 2021 | Medium</title>
    <dc:date>2021-12-13T06:17:17+00:00</dc:date>
    <link>https://medium.com/@fondalee/twitter-is-the-worst-reader-2ac343c41874</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["Twitter is the worst reader" is a brilliant phrase.
]]></description>
<dc:subject>social_media twi twitter re:actually-dr-internet-is-the-name-of-the-monsters-creator to:blog</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:b609277bea41/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:social_media"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:twi"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:twitter"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:re:actually-dr-internet-is-the-name-of-the-monsters-creator"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:blog"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.washingtonpost.com/outlook/2021/10/27/twitter-amplifies-conservative-politicians/">
    <title>Twitter amplifies conservative politicians. Is it because users mock them? - The Washington Post</title>
    <dc:date>2021-10-27T19:55:09+00:00</dc:date>
    <link>https://www.washingtonpost.com/outlook/2021/10/27/twitter-amplifies-conservative-politicians/</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA[In meme form:

https://www.stat.cmu.edu/~cshalizi/dm/20/lectures/23/lecture-23.html#(21)]]></description>
<dc:subject>social_media re:actually-dr-internet-is-the-name-of-the-monsters-creator via:henry_farrell have_read twitter</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:98a731f2b006/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:social_media"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:re:actually-dr-internet-is-the-name-of-the-monsters-creator"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:via:henry_farrell"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:have_read"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:twitter"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.newyorker.com/news/essay/on-the-internet-were-always-famous">
    <title>On the Internet, We’re Always Famous | The New Yorker</title>
    <dc:date>2021-09-27T20:54:33+00:00</dc:date>
    <link>https://www.newyorker.com/news/essay/on-the-internet-were-always-famous</link>
    <dc:creator>cshalizi</dc:creator><dc:subject>moral_psychology hayes.chris re:actually-dr-internet-is-the-name-of-the-monsters-creator social_media to:blog twitter</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:85c69c7def38/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:moral_psychology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:hayes.chris"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:re:actually-dr-internet-is-the-name-of-the-monsters-creator"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:social_media"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:blog"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:twitter"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://endofsafety.substack.com/p/on-those-who-hate-twitter-but-cannot">
    <title>On Those Who Hate Twitter But Cannot Quit It - The End of Safety</title>
    <dc:date>2021-06-09T13:53:01+00:00</dc:date>
    <link>https://endofsafety.substack.com/p/on-those-who-hate-twitter-but-cannot</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA[--- Network externalities, network externalities, network externalities...]]></description>
<dc:subject>twitter cultural_criticism networked_life have_read re:no_one_makes_you_push_to_github</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:456912be5eab/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:twitter"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:cultural_criticism"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:networked_life"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:have_read"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:re:no_one_makes_you_push_to_github"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://arxiv.org/abs/2104.13259">
    <title>[2104.13259] #Trend Alert: How a Cross-Platform Organization Manipulated Twitter Trends in the Indian General Election</title>
    <dc:date>2021-04-29T03:31:36+00:00</dc:date>
    <link>https://arxiv.org/abs/2104.13259</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["Political organizations worldwide keep innovating their use of social media technologies. Here, we document a novel configuration of technologies and organizational forms used to manipulate Twitter trends in the 2019 Indian general election. The organizers rely on an extensive network of WhatsApp groups to coordinate mass-postings by loosely affiliated political supporters. To investigate the campaigns, we joined more than 600 political WhatsApp groups that support the Bharatiya Janata Party, the right-wing party that won the general election. We found direct evidence of 75 hashtag manipulation campaigns, including mobilization messages and lists of pre-written tweets. We estimate the campaigns' size and whether they succeeded in creating controlled social media narratives. We show that the campaigns are smaller than what media reports suggest; still, they reliably produce Twitter trends drawing on the voices of loosely affiliated supporters. Centrally controlled but voluntary in participation, this novel configuration of a campaign complicates the debates over the legitimate use of digital tools for political participation. It may have provided a blueprint for participatory media manipulation by a party with popular support."]]></description>
<dc:subject>to:NB social_media networked_life propaganda deceiving_us_has_become_an_industrial_process india re:actually-dr-internet-is-the-name-of-the-monsters-creator eckles.dean twitter</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:80b3afc6305e/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:social_media"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:networked_life"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:propaganda"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:deceiving_us_has_become_an_industrial_process"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:india"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:re:actually-dr-internet-is-the-name-of-the-monsters-creator"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:eckles.dean"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:twitter"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://arxiv.org/abs/2104.07175">
    <title>[2104.07175] Community-Based Fact-Checking on Twitter's Birdwatch Platform</title>
    <dc:date>2021-04-16T16:07:57+00:00</dc:date>
    <link>https://arxiv.org/abs/2104.07175</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["Misinformation undermines the credibility of social media and poses significant threats to modern societies. As a countermeasure, Twitter has recently introduced "Birdwatch," a community-driven approach to address misinformation on Twitter. On Birdwatch, users can identify tweets they believe are misleading, write notes that provide context to the tweet and rate the quality of other users' notes. In this work, we empirically analyze how users interact with this new feature. For this purpose, we collect all Birdwatch notes and ratings since the introduction of the feature in early 2021. We then map each Birdwatch note to the fact-checked tweet using Twitter's historical API. In addition, we use text mining methods to extract content characteristics from the text explanations in the Birdwatch notes (e.g., sentiment). Our empirical analysis yields the following main findings: (i) users more frequently file Birdwatch notes for misleading than not misleading tweets. These misleading tweets are primarily reported because of factual errors, lack of important context, or because they contain unverified claims. (ii) Birdwatch notes are more helpful to other users if they link to trustworthy sources and if they embed a more positive sentiment. (iii) The helpfulness of Birdwatch notes depends on the social influence of the author of the fact-checked tweet. For influential users with many followers, Birdwatch notes yield a lower level of consensus among users and community-created fact checks are more likely to be seen as being incorrect. Altogether, our findings can help social media platforms to formulate guidelines for users on how to write more helpful fact checks. At the same time, our analysis suggests that community-based fact-checking faces challenges regarding biased views and polarization among the user base."]]></description>
<dc:subject>to:NB social_life_of_the_mind social_media epidemiology_of_representations deceiving_us_has_become_an_industrial_process the_problem_with_peer_review_is_the_peers re:actually-dr-internet-is-the-name-of-the-monsters-creator twitter</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:61408b60873a/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:social_life_of_the_mind"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:social_media"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:epidemiology_of_representations"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:deceiving_us_has_become_an_industrial_process"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:the_problem_with_peer_review_is_the_peers"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:re:actually-dr-internet-is-the-name-of-the-monsters-creator"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:twitter"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://arxiv.org/abs/2006.09938">
    <title>[2006.09938] Did State-sponsored Trolls Shape the 2016 US Presidential Election Discourse? Quantifying Influence on Twitter</title>
    <dc:date>2021-04-16T16:01:00+00:00</dc:date>
    <link>https://arxiv.org/abs/2006.09938</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["It is a widely accepted fact that state-sponsored Twitter accounts operated during the 2016 US presidential election, spreading millions of tweets with misinformation and inflammatory political content. Whether these social media campaigns of the so-called "troll" accounts were able to manipulate public opinion is still in question. Here, we quantify the influence of troll accounts on Twitter by analyzing 152.5 million tweets (by 9.9 million users) from that period. The data contain original tweets from 822 troll accounts identified as such by Twitter itself. We construct and analyse a very large interaction graph of 9.3 million nodes and 169.9 million edges using graph analysis techniques, along with a game-theoretic centrality measure. Then, we quantify the influence of all Twitter accounts on the overall information exchange as is defined by the retweet cascades. We provide a global influence ranking of all Twitter accounts and we find that one troll account appears in the top-100 and four in the top-1000. This combined with other findings presented in this paper constitute evidence that the driving force of virality and influence in the network came from regular users - users who have not been classified as trolls by Twitter. On the other hand, we find that on average, troll accounts were tens of times more influential than regular users were. Moreover, 23% and 22% of regular accounts in the top-100 and top-1000 respectively, have now been suspended by Twitter. This raises questions about their authenticity and practices during the 2016 US presidential election."

--- This doesn't seem to say anything about voting.]]></description>
<dc:subject>to:NB us_politics deceiving_us_has_become_an_industrial_process social_influence social_media information_cascades re:actually-dr-internet-is-the-name-of-the-monsters-creator twitter</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:8ec8009b0053/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:us_politics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:deceiving_us_has_become_an_industrial_process"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:social_influence"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:social_media"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:information_cascades"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:re:actually-dr-internet-is-the-name-of-the-monsters-creator"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:twitter"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://arxiv.org/abs/2003.03667">
    <title>[2003.03667] The growing amplification of social media: Measuring temporal and social contagion dynamics for over 150 languages on Twitter for 2009-2020</title>
    <dc:date>2021-04-10T04:03:05+00:00</dc:date>
    <link>https://arxiv.org/abs/2003.03667</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["Working from a dataset of 118 billion messages running from the start of 2009 to the end of 2019, we identify and explore the relative daily use of over 150 languages on Twitter. We find that eight languages comprise 80% of all tweets, with English, Japanese, Spanish, and Portuguese being the most dominant. To quantify social spreading in each language over time, we compute the 'contagion ratio': The balance of retweets to organic messages. We find that for the most common languages on Twitter there is a growing tendency, though not universal, to retweet rather than share new content. By the end of 2019, the contagion ratios for half of the top 30 languages, including English and Spanish, had reached above 1 -- the naive contagion threshold. In 2019, the top 5 languages with the highest average daily ratios were, in order, Thai (7.3), Hindi, Tamil, Urdu, and Catalan, while the bottom 5 were Russian, Swedish, Esperanto, Cebuano, and Finnish (0.26). Further, we show that over time, the contagion ratios for most common languages are growing more strongly than those of rare languages."]]></description>
<dc:subject>to:NB text_mining social_media twitter</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:a09e3bed177b/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:text_mining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:social_media"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:twitter"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://catalyst-journal.com/vol4/no2/the-poisoned-chalice-of-hashtag-activism">
    <title>The Poisoned Chalice of Hashtag Activism</title>
    <dc:date>2020-12-02T16:25:17+00:00</dc:date>
    <link>https://catalyst-journal.com/vol4/no2/the-poisoned-chalice-of-hashtag-activism</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA[A few comments, not having read the book under discussion:
- I am extremely sympathetic to the viewpoint of the reviewer, that hashtag activism is basically futile.  (If the authors really neglect Tufekci's empirical and theoretical work as much as Frost says they do, it's pretty damning.)
- Not examining right-wing hashtag activism seems like an obvious analytical flaw.  (Even if your primary interest is in left-wing movements, the comparisons would be illuminating.)
- It's true that Twitter isn't accountable to its users, or to the people-as-incorporated-in-government, but Frost for her part never makes clear which of the flaws she identifies would be remedied by such accountability.  
- Doing something about the opioid epidemic by tinkering with drug policy seems a hell of a lot more practical to me that doing something about it by overthrowing American capitalism, or even reversing the trends in inequality over the last half-century.  (I would like to see those trends reversed.)]]></description>
<dc:subject>book_reviews social_media networked_life progressive_forces via:tsuomela twitter the_tyranny_of_structurelessness_rules_everything_around_me re:actually-dr-internet-is-the-name-of-the-monsters-creator blogged</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:b13cdaabaa75/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:book_reviews"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:social_media"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:networked_life"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:progressive_forces"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:via:tsuomela"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:twitter"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:the_tyranny_of_structurelessness_rules_everything_around_me"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:re:actually-dr-internet-is-the-name-of-the-monsters-creator"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:blogged"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.bbc.com/worklife/article/20200123-how-your-twitter-feed-could-help-find-your-dream-job">
    <title>How your Twitter feed could help find your dream job - BBC Worklife</title>
    <dc:date>2020-11-27T06:15:01+00:00</dc:date>
    <link>https://www.bbc.com/worklife/article/20200123-how-your-twitter-feed-could-help-find-your-dream-job</link>
    <dc:creator>cshalizi</dc:creator><dc:subject>twitter text_mining to_teach:data-mining bad_data_analysis to:blog trapped_in_plutos_republic re:career_advising_in_plutos_republic bad_science_journalism</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:b003b2327e6c/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:twitter"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:text_mining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to_teach:data-mining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:bad_data_analysis"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:blog"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:trapped_in_plutos_republic"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:re:career_advising_in_plutos_republic"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:bad_science_journalism"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://nautil.us/blog/scientists-can-predict-your-job-by-your-social_media-personality">
    <title>Twitter Can Help You Match Your Personality to a Career</title>
    <dc:date>2020-11-27T06:14:40+00:00</dc:date>
    <link>http://nautil.us/blog/scientists-can-predict-your-job-by-your-social_media-personality</link>
    <dc:creator>cshalizi</dc:creator><dc:subject>text_mining twitter bad_data_analysis to_teach:data-mining to:blog trapped_in_plutos_republic re:career_advising_in_plutos_republic bad_science_journalism</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:f1c8a863e7dd/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:text_mining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:twitter"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:bad_data_analysis"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to_teach:data-mining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:blog"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:trapped_in_plutos_republic"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:re:career_advising_in_plutos_republic"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:bad_science_journalism"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.pnas.org/content/116/52/26459">
    <title>Social media-predicted personality traits and values can help match people to their ideal jobs | PNAS</title>
    <dc:date>2020-07-16T15:49:42+00:00</dc:date>
    <link>https://www.pnas.org/content/116/52/26459</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["Work is thought to be more enjoyable and beneficial to individuals and society when there is congruence between one’s personality and one’s occupation. We provide large-scale evidence that occupations have distinctive psychological profiles, which can successfully be predicted from linguistic information unobtrusively collected through social media. Based on 128,279 Twitter users representing 3,513 occupations, we automatically assess user personalities and visually map the personality profiles of different professions. Similar occupations cluster together, pointing to specific sets of jobs that one might be well suited for. Observations that contradict existing classifications may point to emerging occupations relevant to the 21st century workplace. Findings illustrate how social media can be used to match people to their ideal occupation."

--- Some observations:
1. They did not actually measure people's personality traits; they _assumed_ that a commercial IBM product can map word usage to personality traits.
1a. In particular, they _assumed_ that this remains accurate for what people write on Twitter, as opposed to whatever context IBM developed their system in (not specified here).
2. They did not actually measure "ideal" occupations; they saw whether a classifier using the estimated personality traits could map people to their actual occupations.
2a. They artificially balance their 10 professions so that each has 955 members.  (I presume that they randomly sampled the occupations with more members, though I don't quite see them saying that; maybe I missed it.  Also, I presume they did _not_ go hunting for the best group of 10 occupations.)  So the baseline accuracy would be only 10%, and getting about 70% under CV does indeed mean that there's some signal here.
2b. It's good that they include error bars on their accuracy figures!
2c.  Since they include those error bars, we can see that the difference in classification accuracy between the different methods are both small and statistically insignificant.  In particular, good old fashioned logistic regression is pretty much on par with everything else.
2d. They don't seem to have actually tried the obvious classifier here, which would map each person to the occupation whose feature-vector center ("medoid") was closest to the person's feature-vector ("prototype method").  But they did at least use k-nearest-neighbors, which performed about as well as all the others.
3. Calling this evidence that we could go from analyzing Twitter word usage to "ideal" job recommendations presumes that most people are _already_ in their ideal jobs.
4. This was edited by Susan Fiske [https://statmodeling.stat.columbia.edu/2017/02/08/authority-figures-spread-happy-talk-still-dont-get-it/].

_Maybe_ people reveal their personalities, in the Big 5 sense, by what they write on Twitter.  (Operationally, "personality" in the Big 5 sense is pretty close to "what words would you use to describe yourself on a questionnaire?")  And _maybe_ the way people reveal their personalities in their word usage on Twitter is so context-independent that it can reliably generalize across all the different sub-cultures and sub-societies and self-organized genre conventions of Twitter, so there is one globally reliable mapping.  (I am not going to repeat all of [http://bactra.org/weblog/770.html], but I could.)  And _maybe_ IBM has provided that mapping with an API.  And _maybe_ people with different personalities select in to different professions.  (As an alternative: different occupations train people differently, which alters their personalities, or at least the verbal expressions thereof, and different occupations expose people to different situations, which alters what they say and maybe even shapes their personalities.)  And _maybe_ people select in to professions where they are happier.  And _maybe_ if we looked at how young people talk on Twitter, before they've chosen an occupation, and extract their personality from it, and map them to a profession with lots of similar personality vectors already in it, they'll be happier in that occupation than in others.  But this study provides at best very, very weak evidence for all this.  (I want to say "no evidence at all", but I also don't want to get into arguments about the theory of evidence.)  What the study does show is that people in different occupations use different words on Twitter, and that these differences are detectable through the filter of IBM's purported personality estimator.

]]></description>
<dc:subject>to:NB have_read bad_science bad_data_analysis classifiers text_mining personality_tests logistic_regression social_media psychology why_oh_why_cant_we_have_a_better_academic_publishing_system to_teach:data-mining forty_minutes_of_my_life_im_not_getting_back trapped_in_plutos_republic to:blog twitter re:career_advising_in_plutos_republic</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:780cca65f6d0/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:have_read"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:bad_science"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:bad_data_analysis"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:classifiers"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:text_mining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:personality_tests"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:logistic_regression"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:social_media"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:psychology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:why_oh_why_cant_we_have_a_better_academic_publishing_system"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to_teach:data-mining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:forty_minutes_of_my_life_im_not_getting_back"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:trapped_in_plutos_republic"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:blog"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:twitter"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:re:career_advising_in_plutos_republic"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.theonion.com/article/twitter-introduces-red-x-mark-verify-users-its-oka-56527">
    <title>Twitter Introduces Red X Mark To Verify Users It’s Okay To Harass - The Onion - America's Finest News Source</title>
    <dc:date>2017-08-03T14:13:33+00:00</dc:date>
    <link>http://www.theonion.com/article/twitter-introduces-red-x-mark-verify-users-its-oka-56527</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["In an effort to reduce the number of unprovoked hostile communications on the social media platform, Twitter announced Monday that it had added a red X-mark feature verifying users who are in fact perfectly okay to harass. “This new verification system offers users a simple, efficient way to determine which accounts belong to total pieces of shit whom you should have no qualms about tormenting to your heart’s desire,” said spokesperson Elizabeth James, adding that the small red symbol signifies that Twitter has officially confirmed the identity of a loathsome person who deserves the worst abuse imaginable and who will deliberately have their Mute, Block, and Report options disabled. “When a user sees this symbol, they know they’re dealing with a real asshole who has richly earned whatever mistreatment they receive, including profanity, body-shaming, leaking of personal information, and relentless goading to commit suicide. It’s really just a helpful way of saying to our users, ‘This fuck has it coming, so do your worst with a clear conscience and without fear of having your account suspended.’” At press time, Twitter reassuredly clarified that the red X was just a suggestion and that all users could still be bullied with as little recourse as they are now."]]></description>
<dc:subject>funny:malicious funny:pointed social_media networked_life twitter re:actually-dr-internet-is-the-name-of-the-monsters-creator</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:918f0c6f6bc6/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:funny:malicious"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:funny:pointed"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:social_media"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:networked_life"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:twitter"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:re:actually-dr-internet-is-the-name-of-the-monsters-creator"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://krugman.blogs.nytimes.com/2012/02/08/the-power-law-of-twitter/">
    <title>The Power (Law) of Twitter - NYTimes.com</title>
    <dc:date>2012-02-08T18:14:11+00:00</dc:date>
    <link>http://krugman.blogs.nytimes.com/2012/02/08/the-power-law-of-twitter/</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA[And here I was worried from the headline that I might have to call out Uncle Paul.]]></description>
<dc:subject>twitter social_media heavy_tails krugman.paul</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:353dc690a140/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:twitter"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:social_media"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:heavy_tails"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:krugman.paul"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://arxiv.org/abs/1110.0535">
    <title>[1110.0535] Modeling the adoption of innovations in the presence of geographic and media influences</title>
    <dc:date>2011-10-05T17:31:16+00:00</dc:date>
    <link>http://arxiv.org/abs/1110.0535</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["While there has been much work examining the affects of social network structure on innovation adoption, models to date have lacked important features such as meta-populations reflecting real geography or influence from mass media forces. In this article, we show these are features crucial to producing more accurate predictions of a social contagion and technology adoption at the city level. Using data from the adoption of the popular micro-blogging platform, Twitter, we present a model of adoption on a network that places friendships in real geographic space and exposes individuals to mass media influence. We show that homopholy both amongst individuals with similar propensities to adopt a technology and geographic location are critical to reproduce features of real spatiotemporal adoption. Furthermore, we estimate that mass media was responsible for increasing Twitter's user base two to four fold. To reflect this strength, we extend traditional contagion models to include an endogenous mass media agent that responds to those adopting an innovation as well as influencing agents to adopt themselves."]]></description>
<dc:subject>diffusion_of_innovations social_influence twitter social_media re:homophily_and_confounding to:NB</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:bcf7d07da1e5/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:diffusion_of_innovations"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:social_influence"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:twitter"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:social_media"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:re:homophily_and_confounding"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://arxiv.org/abs/1107.4009">
    <title>[1107.4009] Social features of online networks: the strength of weak ties in online social media</title>
    <dc:date>2011-07-22T13:05:03+00:00</dc:date>
    <link>http://arxiv.org/abs/1107.4009</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["...Twitter's distinction between different types o interactions allows us to establish a parallelism between online and offline social networks: personal interactions are more likely to occur on internal links of groups (the weakness of strong ties), events transmitting information pass preferentially through links connecting different groups or even more through users acting as bridges between groups (the strength of weak ties)."
]]></description>
<dc:subject>twitter social_media social_networks to:NB re:social_networks_as_sensor_networks</dc:subject>
<dc:identifier>https://pinboard.in/u:cshalizi/b:1e48190e36eb/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:twitter"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:social_media"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:social_networks"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:re:social_networks_as_sensor_networks"/>
</rdf:Bag></taxo:topics>
</item>
</rdf:RDF>