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Abusive language detection models tend to have a problem of being biased toward identity words of a certain group of people because of imbalanced training datasets.
Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean. 2013 · 2013
Earlier work this paper cites.
Learning phrase representations using rnn encoder-decoder for statistical machine translation
Kyunghyun Cho, Bart Van Merriënboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio. 2014 · 2014
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Man is to computer programmer as woman is to homemaker? debiasing word embeddings
Tolga Bolukbasi, Kai-Wei Chang, James Y Zou, Venkatesh Saligrama, and Adam T Kalai. 2016 · 2016
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Are you a racist or am i seeing things? annotator influence on hate speech detection on twitter
Zeerak Waseem. 2016 · 2016
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Hateful symbols or hateful people? predictive features for hate speech detection on twitter
Zeerak Waseem and Dirk Hovy. 2016 · 2016
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Deep learning for hate speech detection in tweets
Pinkesh Badjatiya, Shashank Gupta, Manish Gupta, and Vasudeva Varma. 2017 · 2017
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Enriching word vectors with subword information
Piotr Bojanowski, Edouard Grave, Armand Joulin, and Tomas Mikolov. 2017 · 2017
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Semantics derived automatically from language corpora contain human-like biases
Aylin Caliskan, Joanna J Bryson, and Arvind Narayanan. 2017 · 2017
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Measuring and mitigating unintended bias in text classification
Lucas Dixon, John Li, Jeffrey Sorensen, Nithum Thain, and Lucy Vasserman. 2017 · 2017
Cited alongside, same era.
Using millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasm
Bjarke Felbo, Alan Mislove, Anders Søgaard, Iyad Rahwan, and Sune Lehmann. 2017 · 2017
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Deceiving google’s perspective api built for detecting toxic comments
Hossein Hosseini, Sreeram Kannan, Baosen Zhang, and Radha Poovendran. 2017 · 2017
Cited alongside, same era.
One-step and two-step classification for abusive language detection on twitter
Ji Ho Park and Pascale Fung. 2017 · 2017
Cited alongside, same era.
Ex machina: Personal attacks seen at scale
Ellery Wulczyn, Nithum Thain, and Lucas Dixon. 2017 · 2017
Later among the works it cites.
Data decisions and theoretical implications when adversarially learning fair representations
Alex Beutel, Jilin Chen, Zhe Zhao, and Ed H Chi · 2018
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Large scale crowdsourcing and characterization of twitter abusive behavior
Antigoni-Maria Founta, Constantinos Djouvas, Despoina Chatzakou, Ilias Leontiadis, Jeremy Blackburn, Gianluca Stringhini, Athena Vakali, Michael Sirivianos, and Nicolas Kourtellis. 2018 · 2018
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Examining gender and race bias in two hundred sentiment analysis systems
Svetlana Kiritchenko and Saif M Mohammad. 2018 · 2018
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Mitigating unwanted biases with adversarial learning
Brian Hu Zhang, Blake Lemoine, and Margaret Mitchell. 2018 · 2018
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Gender bias in coreference resolution: Evaluation and debiasing methods
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Deeper attention to abusive user content moderation
John Pavlopoulos, Prodromos Malakasiotis, and Ion Androutsopoulos. 2017 · 2017
Cited alongside, same era.
Jieyu Zhao, Tianlu Wang, Mark Yatskar, Vicente Ordonez, and Kai-Wei Chang. 2018 · 2018
Closest in time.