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Gender Bias in Text: Labeled Datasets and Lexicons. (arXiv:2201.08675v1 [cs.CL])
Jan. 24, 2022, 2:10 a.m. | Jad Doughman, Wael Khreich
cs.CL updates on arXiv.org arxiv.org
Language has a profound impact on our thoughts, perceptions, and conceptions
of gender roles. Gender-inclusive language is, therefore, a key tool to promote
social inclusion and contribute to achieving gender equality. Consequently,
detecting and mitigating gender bias in texts is instrumental in halting its
propagation and societal implications. However, there is a lack of gender bias
datasets and lexicons for automating the detection of gender bias using
supervised and unsupervised machine learning (ML) and natural language
processing (NLP) techniques. Therefore, …
More from arxiv.org / cs.CL updates on arXiv.org
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