The "r'' in "woman'' stands for rights. Auditing LLMs in Uncovering Social Dynamics in Implicit Misogyny
Muti,Arianna Emmery,Chris Nozza,Debora Barrón-Cedeño,Alberto Caselli,Tommaso
Muti,Arianna
Emmery,Chris
Nozza,Debora
Barrón-Cedeño,Alberto
Caselli,Tommaso
Abstract
Persistent societal biases like misogyny express themselves more often implicitly than through openly hostile language.However, previous misogyny studies have focused primarily on explicit language, overlooking these more subtle forms. We bridge this gap by examining implicit misogynistic expressions in English and Italian. First, we develop a taxonomy of social dynamics, i.e., the underlying communicative intent behind misogynistic statements in social media data. Then, we test the ability of nine LLMs to identify the social dynamics as a multi-label classification and text span selection: first LLMs must choose social dynamics given a prefixed list, then they have to explicitly identify the text spans that triggered their decisions. We also investigate the extent of using different learning settings: zero and few-shot, and prescriptive. Our analysis suggests that LLMs struggle to follow instructions and reason in all settings, mostly relying on semantic associations, recasting claims of emergent abilities.
Description
Date
2025-11
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Publisher
Association for Computational Linguistics (ACL)
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Keywords
SDG 5 - Gender Equality
Citation
Muti, A, Emmery, C, Nozza, D, Barrón-Cedeño, A & Caselli, T 2025, The "r'' in "woman'' stands for rights. Auditing LLMs in Uncovering Social Dynamics in Implicit Misogyny. in C Christodoulopoulos, T Chakraborty, C Rose & V Peng (eds), Findings of the Association for Computational Linguistics: EMNLP 2025. Association for Computational Linguistics (ACL), pp. 5462-5479. < https://aclanthology.org/2025.findings-emnlp.292.pdf >