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"Call me sexist, but...": Revisiting Sexism Detection Using Psychological Scales and Adversarial Samples
[article]
2021
arXiv
pre-print
Research has focused on automated methods to effectively detect sexism online. Although overt sexism seems easy to spot, its subtle forms and manifold expressions are not. In this paper, we outline the different dimensions of sexism by grounding them in their implementation in psychological scales. From the scales, we derive a codebook for sexism in social media, which we use to annotate existing and novel datasets, surfacing their limitations in breadth and validity with respect to the
arXiv:2004.12764v2
fatcat:g3sa3dopjrf4dp3xdbjdy2eecq