@inproceedings{lai-etal-2023-werewolf,
    title = "Werewolf Among Us: Multimodal Resources for Modeling Persuasion Behaviors in Social Deduction Games",
    author = "Lai, Bolin  and
      Zhang, Hongxin  and
      Liu, Miao  and
      Pariani, Aryan  and
      Ryan, Fiona  and
      Jia, Wenqi  and
      Hayati, Shirley Anugrah  and
      Rehg, James  and
      Yang, Diyi",
    editor = "Rogers, Anna  and
      Boyd-Graber, Jordan  and
      Okazaki, Naoaki",
    booktitle = "Findings of the Association for Computational Linguistics: ACL 2023",
    month = jul,
    year = "2023",
    address = "Toronto, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.findings-acl.411",
    doi = "10.18653/v1/2023.findings-acl.411",
    pages = "6570--6588",
    abstract = "Persuasion modeling is a key building block for conversational agents. Existing works in this direction are limited to analyzing textual dialogue corpus. We argue that visual signals also play an important role in understanding human persuasive behaviors. In this paper, we introduce the first multimodal dataset for modeling persuasion behaviors. Our dataset includes 199 dialogue transcriptions and videos captured in a multi-player social deduction game setting, 26,647 utterance level annotations of persuasion strategy, and game level annotations of deduction game outcomes. We provide extensive experiments to show how dialogue context and visual signals benefit persuasion strategy prediction. We also explore the generalization ability of language models for persuasion modeling and the role of persuasion strategies in predicting social deduction game outcomes. Our dataset can be found at https://persuasion-deductiongame. socialai-data.org. The codes and models are available at \url{https://github.com/SALT-NLP/PersuationGames}.",
}

Persuasion modeling is a key building block for conversational agents. Existing works in this direction are limited to analyzing textual dialogue corpus. We argue that visual signals also play an important role in understanding human persuasive behaviors. In this paper, we introduce the first multimodal dataset for modeling persuasion behaviors. Our dataset includes 199 dialogue transcriptions and videos captured in a multi-player social deduction game setting, 26,647 utterance level annotations of persuasion strategy, and game level annotations of deduction game outcomes. We provide extensive experiments to show how dialogue context and visual signals benefit persuasion strategy prediction. We also explore the generalization ability of language models for persuasion modeling and the role of persuasion strategies in predicting social deduction game outcomes. Our dataset can be found at https://persuasion-deductiongame. socialai-data.org. The codes and models are available at \url{https://github.com/SALT-NLP/PersuationGames}.
Lai, Bolin Zhang, Hongxin Liu, Miao Pariani, Aryan Ryan, Fiona Jia, Wenqi Hayati, Shirley Anugrah Rehg, James Yang, Diyi
Werewolf Among Us: Multimodal Resources for Modeling Persuasion Behaviors in Social Deduction Games