Abusive Language

45 papers with code • 0 benchmarks • 9 datasets

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Most implemented papers

Racial Bias in Hate Speech and Abusive Language Detection Datasets

unitaryai/detoxify WS 2019

Technologies for abusive language detection are being developed and applied with little consideration of their potential biases.

Comparative Studies of Detecting Abusive Language on Twitter

younggns/comparative-abusive-lang WS 2018

However, this dataset has not been comprehensively studied to its potential.

Understanding Abuse: A Typology of Abusive Language Detection Subtasks

t-davidson/hate-speech-and-offensive-language WS 2017

As the body of research on abusive language detection and analysis grows, there is a need for critical consideration of the relationships between different subtasks that have been grouped under this label.

One-step and Two-step Classification for Abusive Language Detection on Twitter

younggns/comparative-abusive-lang WS 2017

Automatic abusive language detection is a difficult but important task for online social media.

Emo2Vec: Learning Generalized Emotion Representation by Multi-task Training

pxuab/emo2vec_wassa_paper WS 2018

In this paper, we propose Emo2Vec which encodes emotional semantics into vectors.

Sequence Classification with Human Attention

coastalcph/Sequence_classification_with_human_attention CONLL 2018

Learning attention functions requires large volumes of data, but many NLP tasks simulate human behavior, and in this paper, we show that human attention really does provide a good inductive bias on many attention functions in NLP.

Multi-label Hate Speech and Abusive Language Detection in Indonesian Twitter

okkyibrohim/id-multi-label-hate-speech-and-abusive-language-detection WS 2019

Hate speech and abusive language spreading on social media need to be detected automatically to avoid conflict between citizen.

The Discourse of Online Content Moderation: Investigating Polarized User Responses to Changes in Reddit's Quarantine Policy

qinlans/alw3_data WS 2019

Recent concerns over abusive behavior on their platforms have pressured social media companies to strengthen their content moderation policies.