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• W2973192523 abstract "In this work, we investigate the presence of occupational gender stereotypes in sentiment analysis models. Such a task has implications in reducing implicit biases in these models, which are being applied to an increasingly wide variety of downstream tasks. We release a new gender-balanced dataset of 800 sentences pertaining to specific professions and propose a methodology for using it as a test bench to evaluate sentiment analysis models. We evaluate the presence of occupational gender stereotypes in 3 different models using our approach, and explore their relationship with societal perceptions of occupations." @default.
• W2973192523 created "2019-09-19" @default.
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• W2973192523 date "2019-01-01" @default.
• W2973192523 modified "2023-09-25" @default.
• W2973192523 title "Good Secretaries, Bad Truck Drivers? Occupational Gender Stereotypes in Sentiment Analysis" @default.
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• W2973192523 doi "https://doi.org/10.18653/v1/w19-3809" @default.
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