Papers by Laura Vianna

2 papers
Beyond Denouncing Hate: Strategies for Countering Implied Biases and Stereotypes in Language (2023.findings-emnlp)

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Challenge: Counterspeech, i.e. responses to counteract potential harms of hateful speech, has become an increasingly popular solution to address online hate speech without censorship risks of deletion-based content moderation.
Approach: They draw from psychology and philosophy literature to craft six psychologically inspired strategies to challenge the underlying stereotypical implications of hateful language.
Outcome: The strategies used in human- and machine-generated counterspeech datasets are convincing, whereas human-written counterspech uses less specific strategies compared to machine-produced counters.
Annotators with Attitudes: How Annotator Beliefs And Identities Bias Toxic Language Detection (2022.naacl-main)

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Challenge: toxicity annotations are often ignored because of its subjective nature and lack of nuance.
Approach: They examine the effect of annotator identities and beliefs on toxic language annotations by considering posts with three characteristics: anti-Black language, African American English (AAE) dialect, and vulgarity.
Outcome: The findings show strong associations between annotator identity and beliefs and ratings of toxicity.

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