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Studying evolution of fake news to hate speech

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dc.contributor.author Goel, Vasu
dc.contributor.author Sahnan, Dhruv
dc.contributor.author Chakraborty, Tanmoy (Advisor)
dc.date.accessioned 2023-04-14T11:48:58Z
dc.date.available 2023-04-14T11:48:58Z
dc.date.issued 2021-05
dc.identifier.uri http://repository.iiitd.edu.in/xmlui/handle/123456789/1150
dc.description.abstract Curbing hate speech is undoubtedly a major challenge for online microblogging platforms like Twitter. While there have been studies around hate speech detection, it is not clear how hate speech _nds its way into an online discussion. It is important for a content moderator to not only identify which tweet is hateful, but also to predict which tweet will be responsible for accumu-lating hate speech. This would help in prioritizing tweets that need constant monitoring. Our analysis reveals that for hate speech to manifest in an ongoing discussion, the source tweet may not necessarily be hateful; rather, there are plenty of such non-hateful tweets which gradually invoke hateful replies, resulting in the entire reply threads becoming provocative. en_US
dc.language.iso en_US en_US
dc.publisher IIIT-Delhi en_US
dc.subject Machine Learning en_US
dc.subject Natural Language Processing en_US
dc.subject Fake News en_US
dc.subject Hate Speech en_US
dc.subject Pro le Clustering en_US
dc.title Studying evolution of fake news to hate speech en_US


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