Modeling the Impact of Group Interactions on Climate-related Opinion Change in Reddit
Alessia Antelmi, Carmine Spagnuolo, and Luca Maria Aiello

TL;DR
This paper introduces a temporal hypergraph model to better capture group interactions in social media discussions about climate change on Reddit, improving predictions of opinion shifts over traditional dyadic models.
Contribution
The study presents a novel hypergraph-based approach for modeling group dynamics in online discussions, validated against large language model annotations, outperforming traditional dyadic models.
Findings
Hypergraph model predicts opinion shifts more accurately.
Group interactions significantly influence opinion dynamics.
Model outperforms dyadic interaction models.
Abstract
Opinion dynamics models describe the evolution of behavioral changes within social networks and are essential for informing strategies aimed at fostering positive collective changes, such as climate action initiatives. When applied to social media interactions, these models typically represent social exchanges in a dyadic format to allow for a convenient encoding of interactions into a graph where edges represent the flow of information from one individual to another. However, this structural assumption fails to adequately reflect the nature of group discussions prevalent on many social media platforms. To address this limitation, we present a temporal hypergraph model that effectively captures the group dynamics inherent in conversational threads, and we apply it to discussions about climate change on Reddit. This model predicts temporal shifts in stance towards climate issues at the…
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Taxonomy
TopicsOpinion Dynamics and Social Influence · Misinformation and Its Impacts · Complex Network Analysis Techniques
