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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Investigating the Validity of Botometer-based Social Bot Studies · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2207.11474/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/2207.11474/feed.xml" rel="self" type="application/rss+xml" /><item><title>Investigating the Validity of Botometer-based Social Bot Studies — mentioned by mike_hearn</title><link>https://news.ycombinator.com/item?id=32361296</link><guid isPermaLink="false">urn:hackerpapers:mention:2207.11474:32361296</guid><pubDate>Fri, 05 Aug 2022 20:04:26 GMT</pubDate><description>&lt;p&gt;Urgh, Botometer. I guessed it would be that as soon as I saw the headline. I used to work on fighting bots. Botometer has a long and storied history of making totally false claims about Twitter accounts. In the past it identified something like 50% of US Congress as bots. It has unfortunate credibility because it&amp;#x27;s a machine learning model produced by academic &amp;quot;research&amp;quot;, but no credibility is deserved. The academics who created it are, in my view, guilty of gross intellectual misconduct. Botometer has had an absurdly high FP rate for years and Twitter are right to call Musk out for using it…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2207.11474/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.SI</category></item></channel></rss>
