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20172021
most citedMitigating Gender Bias in Natural Language Processing: Literature Review

42 citations · 43 across the 4 of their papers we have counts for

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6 papers · 1 filter

cs.CL2019

A Benchmark Dataset for Learning to Intervene in Online Hate Speech

Jing Qian, Anna Bethke, Yinyin Liu +2

Countering online hate speech is a critical yet challenging task, but one which can be aided by the use of Natural Language Processing (NLP) techniques. Previous research has prima…

cs.CL201942 cited

Mitigating Gender Bias in Natural Language Processing: Literature Review

Tony Sun, Andrew Gaut, Shirlyn Tang +7

As Natural Language Processing (NLP) and Machine Learning (ML) tools rise in popularity, it becomes increasingly vital to recognize the role they play in shaping societal biases an…

cs.CL2019

Learning to Decipher Hate Symbols

Jing Qian, Mai ElSherief, Elizabeth Belding +1

Existing computational models to understand hate speech typically frame the problem as a simple classification task, bypassing the understanding of hate symbols (e.g., 14 words, ki…

cs.CL2018

Hierarchical CVAE for Fine-Grained Hate Speech Classification

Jing Qian, Mai ElSherief, Elizabeth Belding +1

Existing work on automated hate speech detection typically focuses on binary classification or on differentiating among a small set of categories. In this paper, we propose a novel…

cs.CL2018

Hate Lingo: A Target-based Linguistic Analysis of Hate Speech in Social Media

Mai ElSherief, Vivek Kulkarni, Dana Nguyen +2

While social media empowers freedom of expression and individual voices, it also enables anti-social behavior, online harassment, cyberbullying, and hate speech. In this paper, we…

cs.CL2018

Leveraging Intra-User and Inter-User Representation Learning for Automated Hate Speech Detection

Jing Qian, Mai ElSherief, Elizabeth M. Belding +1

Hate speech detection is a critical, yet challenging problem in Natural Language Processing (NLP). Despite the existence of numerous studies dedicated to the development of NLP hat…