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Towards Lexical Gender Inference: A Scalable Methodology using Online Databases

arXiv 2206.14055 ↗First posted 28 Jun 2022cs.CLcited by 0

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Abstract (arXiv)

This paper presents a new method for automatically detecting words with lexical gender in large-scale language datasets. Currently, the evaluation of gender bias in natural language processing relies on manually compiled lexicons of gendered expressions, such as pronouns ('he', 'she', etc.) and nouns with lexical gender ('mother', 'boyfriend', 'policewoman', etc.). However, manual compilation of such lists can lead to static information if they are not periodically updated and often involve value judgments by individual annotators and researchers. Moreover, terms not included in the list fall out of the range of analysis. To address these issues, we devised a scalable, dictionary-based method to automatically detect lexical gender that can provide a dynamic, up-to-date analysis with high coverage. Our approach reaches over 80% accuracy in determining the lexical gender of nouns retrieved randomly from a Wikipedia sample and when testing on a list of gendered words used in previous research.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 17 of its 38 references that are in the map. First posted on arXiv 28 Jun 2022.

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References · 17

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  11. 2020Detecting Emergent Intersectional Biases: Contextualized Word Embeddings Contain a Distribution of Human-like Biasescited by 167
  12. 2019It's All in the Name: Mitigating Gender Bias with Name-Based Counterfactual Data Substitutioncited by 103
5 more
  1. 2019Toward Gender-Inclusive Coreference Resolutioncited by 84
  2. 2020Unmasking Contextual Stereotypes: Measuring and Mitigating BERT's Gender Biascited by 82
  3. 2021Changing the World by Changing the Datacited by 51
  4. 2021NeuTral Rewriter: A Rule-Based and Neural Approach to Automatic Rewriting into Gender-Neutral Alternativescited by 46
  5. 2015It's a Man's Wikipedia? Assessing Gender Inequality in an Online Encyclopediacited by 30

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