Papers by Tom Bourgeade

3 papers
Humans Need Context, What about Machines? Investigating Conversational Context in Abusive Language Detection (2024.lrec-main)

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Challenge: In this paper, we examine the role of conversational context in abusive language detection . prior studies have ignored the contextual nature of abusive language, ignoring this aspect . toxicity, hate speech, harmful stereotypes are among the forms of harmful language .
Approach: They propose to use conversational context to analyze abusive language detection using two methods . they use "abusive language" as an umbrella term to refer to various forms of harmful language .
Outcome: The proposed approach is based on two datasets in English and a new dataset of French tweets annotated for hate speech and stereotypes.
What Did You Learn To Hate? A Topic-Oriented Analysis of Generalization in Hate Speech Detection (2023.eacl-main)

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Challenge: Hate speech detection datasets often use different annotation guidelines, resulting in inconsistencies . authors propose a topic-oriented approach to study generalization across popular hate speech datasets .
Approach: They propose a topic-oriented approach to study generalization across popular hate speech datasets . they compare Transformer-based models in capturing topic-generic and topic-specific knowledge .
Outcome: The proposed approach improves the reliability of hate speech detection on social media platforms.
A Multilingual Dataset of Racial Stereotypes in Social Media Conversational Threads (2023.findings-eacl)

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Challenge: a new corpus-based study addresses racial stereotypes in social media conversations . a multilingual corpus of rhs is used to investigate how they are spread .
Approach: They propose a corpus-based method for multilingual racial stereotype identification in social media conversational threads.
Outcome: The proposed method sheds light on how racial hoaxes are spread and allows identification of negative stereotypes that reinforce them.

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