Angry Men, Sad Women: Large Language Models Reflect Gendered Stereotypes in Emotion Attribution

---

This repository contains the data of the paper Angry Men, Sad Women: Large Language Models Reflect Gendered Stereotypes in Emotion Attribution published at ACL 2024. See the paper for additional details:

Plaza-del-Arco, F. M., Curry, A. C., Curry, A., Abercrombie, G., & Hovy, D. (2024). Angry Men, Sad Women: Large Language Models Reflect Gendered Stereotypes in Emotion Attribution. arXiv preprint arXiv:2403.03121. Link.

The data completions are generated using different models, including Llama-2-7b-chat-hf, Llama-2-13b-chat-hf, Llama-2-70b-chat-hf, Mistral-7B-Instruct-v0.1, and gpt-4.

Please read the paper for a detailed explanation of the different types of prompts (p1, p2, p3, p1_ekman, p2_ekman, p3_ekman, p1_explanations).

License

Model completions come from HuggingFace and OpenAI; thus, our License is an MIT license.

Citation

@inproceedings{plaza-del-arco-etal-2024-emotion-gendered-stereotypes,
      title={{Angry Men, Sad Women: Large Language Models Reflect Gendered Stereotypes in Emotion Attribution}},
      author={{Plaza-del-Arco}, {Flor Miriam} and {Cercas Curry}, Amanda and Curry, Alba and Abercrombie, Gavin and Hovy, Dirk},
      journal={arXiv preprint arXiv:2403.03121},
      year={2024}
}