Beyond Polarization: Opinion Mixing and Social Influence in Deliberation
Mohak Goyal, Lodewijk Gelauff, Naman Gupta, Ashish Goel, and Kamesh Munagala

TL;DR
This study introduces opinion mixing as a new way to measure opinion change in deliberation, showing that deliberation often reshuffles opinions rather than simply increasing or decreasing polarization, with implications for understanding social influence.
Contribution
The paper presents a novel metric called opinion mixing, demonstrates its effectiveness across large international datasets, and links discussion quality to opinion shifts using AI-assisted coding.
Findings
Deliberation increases opinion mixing in most cases.
Standard polarization metrics show heterogeneous results.
Support and justification in discussions predict opinion shifts.
Abstract
Deliberative processes are often discussed as increasing or decreasing polarization. This approach misses a different, and arguably more diagnostic, dimension of opinion change: whether deliberation reshuffles who agrees with whom, or simply moves everyone in parallel while preserving the pre-deliberation rank ordering. We introduce \opinion mixing, measured by Kendall's rank correlation (\tau) between pre- and post-deliberation responses, as a complement to variance-based polarization metrics. Across two large online deliberative polls spanning 32 countries (MCF-2022: n=6,342; MCF-2023: n=1,529), deliberation increases opinion mixing relative to survey-only controls: treatment groups exhibit lower rank correlation on (97%) and (93%) of opinion questions, respectively. Polarization measures based on variance tell a more heterogeneous story: controls consistently converge, while treated…
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Taxonomy
TopicsSocial Media and Politics · Opinion Dynamics and Social Influence · Misinformation and Its Impacts
