Conference Paper Published
Study
Experience and Opportunities
| Luo, X., Lok, W. H., & Hsu, Y. Y. (2025). ‘But this one was so . . . male.’ A Corpus-Based and LLM-Augmented Analysis of Language and Gender Bias in Barbie. In Proceedings of the 39th Pacific Asia Conference on Language, Information and Computation, 245-253. |
| URL: https://aclanthology.org/2025.paclic-1.21/ |
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Abstract The 2023 film Barbie has sparked discussions on women’s empowerment and patriarchal norms, weaving feminist themes with critiques of gender roles while subtly reflecting patriarchal undertones that marginalize women (Myisha et al., 2023). We conduct a corpus-based analysis to investigate gender bias and differences in utterances’ distribution of part-of-speech (POS), affective values, and gender-linked classifications across three distinct scenes: 1) Barbie Land, 2) Real World, and 3) Post-Barbie Land, each representing the matriarchal, conventional and patriarchal theme, respectively. Leveraging large language models (LLMs), we extend Bradley and Lang’s (1999) affective norms to assess the emotional properties of film scripts, marking a novel application of LLMs in film script analysis. |
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