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Little attention is placed on analyzing nationality bias in language models, especially when nationality is highly used as a factor in increasing the performance of social NLP models.
When news reporters deceive: The production of stereotypes
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Representations of africa in the western news media: Reinforcing myths and stereotypes
Amy E Harth. 2012 · 2012
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Vader: A parsimonious rule-based model for sentiment analysis of social media text
Clayton Hutto and Eric Gilbert. 2014 · 2014
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Individuals using the internet (% of population) - united states
WorldBank. 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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Classification and its consequences for online harassment: Design insights from heartmob
Lindsay Blackwell, Jill Dimond, Sarita Schoenebeck, and Cliff Lampe. 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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The new 4.3 billion word now corpus, with 4–5 million words of data added every day
Mark Davies. 2017 · 2017
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textblob documentation
Steven Loria. 2018 · 2018
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Gender bias in coreference resolution
Rachel Rudinger, Jason Naradowsky, Brian Leonard, and Benjamin Van Durme. 2018 · 2018
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Measuring bias in contextualized word representations
Keita Kurita, Nidhi Vyas, Ayush Pareek, Alan W Black, and Yulia Tsvetkov. 2019 · 2019
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Perturbation sensitivity analysis to detect unintended model biases
Vinodkumar Prabhakaran, Ben Hutchinson, and Margaret Mitchell. 2019 · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al. 2019 · 2019
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Universal adversarial triggers for attacking and analyzing nlp
Eric Wallace, Shi Feng, Nikhil Kandpal, Matt Gardner, and Sameer Singh. 2019 · 2019
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Disability, bias, and ai
Meredith Whittaker, Meryl Alper, Cynthia L Bennett, Sara Hendren, Liz Kaziunas, Mara Mills, Meredith Ringel Morris, Joy Rankin, Emily Rogers, Marcel Salas, et al. 2019 · 2019
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A snapshot of the frontiers of fairness in machine learning
Persistent anti-muslim bias in large language models
Abubakar Abid, Maheen Farooqi, and James Zou. 2021 · 2021
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On the dangers of stochastic parrots: Can language models be too big?
Emily M Bender, Timnit Gebru, Angelina McMillan-Major, and Shmargaret Shmitchell. 2021 · 2021
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Quantifying social biases in nlp: A generalization and empirical comparison of extrinsic fairness metrics
Paula Czarnowska, Yogarshi Vyas, and Kashif Shah. 2021 · 2021
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Empathbert: A bert-based framework for demographic-aware empathy prediction
Bhanu Prakash Reddy Guda, Aparna Garimella, and Niyati Chhaya. 2021 · 2021
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Stereoset: Measuring stereotypical bias in pretrained language models
Moin Nadeem, Anna Bethke, and Siva Reddy. 2021 · 2021
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Alexandra Chouldechova and Aaron Roth. 2020 · 2020
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On measuring and mitigating biased inferences of word embeddings
Sunipa Dev, Tao Li, Jeff M Phillips, and Vivek Srikumar. 2020 · 2020
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Polibert: Classifying political social media messages with bert
Shloak Gupta, S Bolden, Jay Kachhadia, A Korsunska, and J Stromer-Galley. 2020 · 2020
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Social biases in nlp models as barriers for persons with disabilities
Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020 · 2020
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Contextualizing hate speech classifiers with post-hoc explanation
Brendan Kennedy, Xisen Jin, Aida Mostafazadeh Davani, Morteza Dehghani, and Xiang Ren. 2020 · 2020
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Probing toxic content in large pre-trained language models
Nedjma Ousidhoum, Xinran Zhao, Tianqing Fang, Yangqiu Song, and Dit-Yan Yeung. 2021 · 2021
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A hybrid approach of opinion mining and comparative linguistic analysis of restaurant reviews
Salim Sazzed. 2021 · 2021
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Pranav Narayanan Venkit and Shomir Wilson. 2021 · 2021
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On measures of biases and harms in nlp
Sunipa Dev, Emily Sheng, Jieyu Zhao, Aubrie Amstutz, Jiao Sun, Yu Hou, Mattie Sanseverino, Jiin Kim, Akihiro Nishi, Nanyun Peng, et al. 2022 · 2022
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A study of implicit bias in pretrained language models against people with disabilities
Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022 · 2022
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