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With the recent proliferation of the use of text classifications, researchers have found that there are certain unintended biases in text classification datasets.
Inference and missing data
Donald B Rubin. 1976 · 1976
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Sample selection bias as a specification error
James J Heckman. 1979 · 1979
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The central role of the propensity score in observational studies for causal effects
Paul R Rosenbaum and Donald B Rubin. 1983 · 1983
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Improving predictive inference under covariate shift by weighting the log-likelihood function
Hidetoshi Shimodaira. 2000 · 2000
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Learning and evaluating classifiers under sample selection bias
Bianca Zadrozny. 2004 · 2004
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An improved categorization of classifier’s sensitivity on sample selection bias
Wei Fan, Ian Davidson, Bianca Zadrozny, and Philip S Yu. 2005 · 2005
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Analysis of representations for domain adaptation
Shai Ben-David, John Blitzer, Koby Crammer, and Fernando Pereira. 2007 · 2007
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Instance weighting for domain adaptation in nlp
Jing Jiang and ChengXiang Zhai. 2007 · 2007
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Selection bias in web surveys and the use of propensity scores
Matthias Schonlau, Arthur Van Soest, Arie Kapteyn, and Mick Couper. 2009 · 2009
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Three naive bayes approaches for discrimination-free classification
Toon Calders and Sicco Verwer. 2010 · 2010
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Fairness through awareness
Cynthia Dwork, Moritz Hardt, Toniann Pitassi, Omer Reingold, and Richard Zemel. 2012 · 2012
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Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher Manning. 2014 · 2014
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Moving towards best practice when using inverse probability of treatment weighting (iptw) using the propensity score to estimate causal treatment effects in observational studies
Peter C Austin and Elizabeth A Stuart. 2015 · 2015
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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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Semantics derived automatically from language corpora necessarily contain human biases
Aylin Caliskan-Islam, Joanna J. Bryson, and Arvind Narayanan. 2016 · 2016
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On the (im) possibility of fairness
Sorelle A Friedler, Carlos Scheidegger, and Suresh Venkatasubramanian. 2016 · 2016
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Men also like shopping: Reducing gender bias amplification using corpus-level constraints
Jieyu Zhao, Tianlu Wang, Mark Yatskar, Vicente Ordonez, and Kai-Wei Chang. 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. 2018 · 2018
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Examining gender and race bias in two hundred sentiment analysis systems
Svetlana Kiritchenko and Saif Mohammad. 2018 · 2018
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Reducing gender bias in abusive language detection
Ji Ho Park, Jamin Shin, and Pascale Fung. 2018 · 2018
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Position bias estimation for unbiased learning to rank in personal search
Xuanhui Wang, Nadav Golbandi, Michael Bendersky, Donald Metzler, and Marc Najork. 2018 · 2018
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Mitigating unwanted biases with adversarial learning
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Equality of opportunity in supervised learning
Moritz Hardt, Eric Price, Nati Srebro, et al. 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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Data decisions and theoretical implications when adversarially learning fair representations
Alex Beutel, Ed H Chi, Jilin Chen, and Zhe Zhao. 2017 · 2017
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Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
Alexandra Chouldechova. 2017 · 2017
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Unbiased learning-to-rank with biased feedback
Thorsten Joachims, Adith Swaminathan, and Tobias Schnabel. 2017 · 2017
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Brian Hu Zhang, Blake Lemoine, and Margaret Mitchell. 2018 · 2018
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Gender bias in coreference resolution: Evaluation and debiasing methods
Jieyu Zhao, Tianlu Wang, Mark Yatskar, Vicente Ordonez, and Kai-Wei Chang. 2018 · 2018
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Nuanced metrics for measuring unintended bias with real data for text classification
Daniel Borkan, Lucas Dixon, Jeffrey Sorensen, Nithum Thain, and Lucy Vasserman. 2019 · 2019
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Mitigating gender bias in natural language processing: Literature review
Tony Sun, Andrew Gaut, Shirlyn Tang, Yuxin Huang, Mai ElSherief, Jieyu Zhao, Diba Mirza, Elizabeth Belding, Kai-Wei Chang, and William Yang Wang. 2019 · 2019
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Selection bias explorations and debias methods for natural language sentence matching datasets
Guanhua Zhang, Bing Bai, Jian Liang, Kun Bai, Shiyu Chang, Mo Yu, Conghui Zhu, and Tiejun Zhao. 2019 · 2019
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