What you say or how you say it? Predicting Conflict Outcomes in Real and LLM-Generated Conversations
Keywords: Conflict, conversations, communication features analysis, Reddit discussions, Social Computing Systems.
TL;DR: This paper integrates content- and expression-based approaches to conflict by analyzing 191 communication features across simulated GPT-4 conversations and real-world Reddit discussions to predict destructive conflict outcomes.
Abstract: When conflicts escalate, is it due to what is said or how it is said? In the conflict literature, two theoretical approaches take opposing views: one focuses on the content of the disagreement, while the other focuses on how it is expressed. This paper aims to integrate these two perspectives through a computational analysis of 191 communication features — 128 related to expression and 63 to content. We analyze 1,200 GPT-4 simulated conversations and 12,630 real-world discussions from Reddit. We find that expression features more reliably predict destructive conflict outcomes across both settings, although the most important features differ. In the Reddit data, conversational dynamics such as turn-taking and conversational equality are highly predictive, but they are not predictive in simulated conversations. These results may suggest a possible limitation in simulating social interactions with language models, and we discuss the implications for our findings on building social computing systems.
Submission Number: 73
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