mlsanityData to 14 Oct 2026

Good Secretaries, Bad Truck Drivers? Occupational Gender Stereotypes in Sentiment Analysis

arXiv 1906.10256 ↗First posted 24 Jun 2019cs.CLcited by 19

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Abstract (arXiv)

In this work, we investigate the presence of occupational gender stereotypes in sentiment analysis models. Such a task has implications for 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.

Key facts. Cited by 19 papers in the map (data through 14 Oct 2026). First posted on arXiv 24 Jun 2019.

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Citing papers per year: 2021: 2; 2022: 3; 2023: 9; 2024: 2; 2025: 3.

19 papers.

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  1. 2023Having Beer after Prayer? Measuring Cultural Bias in Large Language Modelscited by 153
  2. 2021A Survey on Gender Bias in Natural Language Processingcited by 89
  3. 2021Quantifying Social Biases in NLP: A Generalization and Empirical Comparison of Extrinsic Fairness Metricscited by 83
  4. 2022Theories of "Gender" in NLP Bias Researchcited by 62
  5. 2023Sociodemographic Bias in Language Models: A Survey and Forward Pathcited by 28
  6. 2023''Fifty Shades of Bias'': Normative Ratings of Gender Bias in GPT Generated English Textcited by 15
  7. 2023CALM : A Multi-task Benchmark for Comprehensive Assessment of Language Model Biascited by 14
  8. 2023The Sentiment Problem: A Critical Survey towards Deconstructing Sentiment Analysiscited by 12
  9. 2023In the Name of Fairness: Assessing the Bias in Clinical Record De-identificationcited by 9
  10. 2022Towards an Enhanced Understanding of Bias in Pre-trained Neural Language Models: A Survey with Special Emphasis on Affective Biascited by 8
  11. 2022Measuring Harmful Representations in Scandinavian Language Modelscited by 7
  12. 2025Colombian Waitresses y Jueces canadienses: Gender and Country Biases in Occupation Recommendations from LLMscited by 7
7 more
  1. 2024Measuring Machine Learning Harms from Stereotypes Requires Understanding Who Is Harmed by Which Errors in What Wayscited by 4
  2. 2023Measuring Normative and Descriptive Biases in Language Models Using Census Datacited by 3
  3. 2024Are Female Carpenters like Blue Bananas? A Corpus Investigation of Occupation Gender Typicalitycited by 3
  4. 2025Measuring Gender Bias in Job Title Matching for Grammatical Gender Languagescited by 2
  5. 2023Blacks is to Anger as Whites is to Joy? Understanding Latent Affective Bias in Large Pre-trained Neural Language Modelscited by 0
  6. 2023Learning Horn Envelopes via Queries from Large Language Modelscited by 0
  7. 2025Exploring Gender Bias Beyond Occupational Titlescited by 0