Web: http://arxiv.org/abs/2201.08451

Jan. 24, 2022, 2:10 a.m. | Austin van Loon, Salvatore Giorgi, Robb Willer, Johannes Eichstaedt

cs.LG updates on arXiv.org arxiv.org

The word embedding association test (WEAT) is an important method for
measuring linguistic biases against social groups such as ethnic minorities in
large text corpora. It does so by comparing the semantic relatedness of words
prototypical of the groups (e.g., names unique to those groups) and attribute
words (e.g., 'pleasant' and 'unpleasant' words). We show that anti-black WEAT
estimates from geo-tagged social media data at the level of metropolitan
statistical areas strongly correlate with several measures of racial
animus--even when …

arxiv bias negative word embeddings

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