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Title: Identifying Power Relations in Conversations using Multi-Agent Social Reasoning
Large language models (LLMs) struggle in social science domains, where critical thinking and human-level inference are crucial. In this work, we propose a multi-agent social reasoning framework that leverages the generative and reasoning capabilities of LLMs to generate and evaluate reasons from multiple perspectives grounded in social science theories, and construct a factor graph for inference. Experimental results on understanding power dynamics in conversations show that our method outperforms standard prompting baselines, demonstrating its potential for tackling hard Computational Social Science (CSS) tasks.  more » « less
Award ID(s):
2048001
PAR ID:
10590741
Author(s) / Creator(s):
; ; ;
Publisher / Repository:
Association for Computational Linguistics
Date Published:
Page Range / eLocation ID:
855 to 865
Format(s):
Medium: X
Location:
Albuquerque, New Mexico
Sponsoring Org:
National Science Foundation
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