Discovering and Interpreting Biased Concepts in Online Communities. (arXiv:2010.14448v2 [cs.CL] UPDATED)

Web: http://arxiv.org/abs/2010.14448

Language carries implicit human biases, functioning both as a reflection and
a perpetuation of stereotypes that people carry with them. Recently, ML-based
NLP methods such as word embeddings have been shown to learn such language
biases with striking accuracy. This capability of word embeddings has been
successfully exploited as a tool to quantify and study human biases. However,
previous studies only consider a predefined set of biased concepts to attest
(e.g., whether gender is more or less associated with particular …

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