Modeling Constraints Can Identify Winning Arguments in Multi-Party Interactions (Student Abstract)

Suzanna Sia, Kokil Jaidka, Niyati Chayya, Kevin Duh

AAAI 2022 pp. 13049-13050

doi:10.1609/AAAI.V36I11.21661 /aaai/2022/sia2022aaai-modeling/

Abstract

In contexts where debate and deliberation is the norm, participants are regularly presented with new information that conflicts with their original beliefs. When required to update their beliefs (belief alignment), they may choose arguments that align with their worldview (confirmation bias). We test this and competing hypotheses in a constraint-based modeling approach to predict the winning arguments in multi-party interactions in the Reddit ChangeMyView dataset. We impose structural constraints that reflect competing hypotheses on a hierarchical generative Variational Auto-encoder. Our findings suggest that when arguments are further from the initial belief state of the target, they are more likely to succeed.

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Cite

Text

Sia et al. "Modeling Constraints Can Identify Winning Arguments in Multi-Party Interactions (Student Abstract)." AAAI Conference on Artificial Intelligence, 2022. doi:10.1609/AAAI.V36I11.21661

Markdown

[Sia et al. "Modeling Constraints Can Identify Winning Arguments in Multi-Party Interactions (Student Abstract)." AAAI Conference on Artificial Intelligence, 2022.](https://mlanthology.org/aaai/2022/sia2022aaai-modeling/) doi:10.1609/AAAI.V36I11.21661

BibTeX

@inproceedings{sia2022aaai-modeling,
  title     = {{Modeling Constraints Can Identify Winning Arguments in Multi-Party Interactions (Student Abstract)}},
  author    = {Sia, Suzanna and Jaidka, Kokil and Chayya, Niyati and Duh, Kevin},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2022},
  pages     = {13049-13050},
  doi       = {10.1609/AAAI.V36I11.21661},
  url       = {https://mlanthology.org/aaai/2022/sia2022aaai-modeling/}
}