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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Racial Bias in Hate Speech and Abusive Language Detection Datasets · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1905.12516/</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/1905.12516/feed.xml" rel="self" type="application/rss+xml" /><item><title>Racial Bias in Hate Speech and Abusive Language Detection Datasets — mentioned by Ar-Curunir</title><link>https://news.ycombinator.com/item?id=31702233</link><guid isPermaLink="false">urn:hackerpapers:mention:1905.12516:31702233</guid><pubDate>Sat, 11 Jun 2022 05:38:36 GMT</pubDate><description>&lt;p&gt;The original paper (https://arxiv.org/pdf/1905.12516.pdf) draws a different conclusion from what the article claims. Read Section 5 (Discussion) for details. Also, the analysis seems to be limited to looking at just two words, and to two groups (black and white), so I&amp;#x27;m not sure how this generalizes. (the latter also makes the title of the post incorrect) The OP post is also a right-wing-nonsense website that can&amp;#x27;t even get the affiliation of the authors correct (&amp;quot;University of Cornell&amp;quot;). Mods, please replace the link with a link to the paper, or to a more reputable academic source.&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1905.12516/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item><item><title>Racial Bias in Hate Speech and Abusive Language Detection Datasets — mentioned by visarga</title><link>https://news.ycombinator.com/item?id=31702232</link><guid isPermaLink="false">urn:hackerpapers:mention:1905.12516:31702232</guid><pubDate>Sat, 11 Jun 2022 05:38:15 GMT</pubDate><description>&lt;p&gt;Found the same story published 3 years ago with better title: &amp;quot;Study finds racial bias in tweets flagged as hate speech&amp;quot; https://as.cornell.edu/news/study-finds-racial-bias-tweets-f... &amp;gt;“When we as researchers, or the people we pay online to do crowdsourced annotation, look at these tweets and have to decide, ‘Is this hateful or not hateful?’ we may see language written in what linguists consider African American English and be more likely to think that it’s something that is offensive due to our own internal biases,” Davidson said. “We want people annotating data to be aware of the nuances…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1905.12516/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item><item><title>Racial Bias in Hate Speech and Abusive Language Detection Datasets — HN submission</title><link>https://news.ycombinator.com/item?id=31688512</link><guid isPermaLink="false">urn:hackerpapers:submission:1905.12516:31688512</guid><pubDate>Fri, 10 Jun 2022 00:09:13 GMT</pubDate><description>&lt;p&gt;Racial Bias in Hate Speech and Abusive Language Detection Datasets&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;5 points; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/1905.12516/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item></channel></rss>
