Sentiment spreads, but topics do not, in COVID-19 discussions within the Belgian Reddit community
Tim Van Wesemael, Luis E. C. Rocha, Tijs W. Alleman, Jan M. Baetens

TL;DR
This study analyzes COVID-19 discussions on Belgian Reddit, revealing that while topic volume correlates with external events, sentiment spreads through user interactions, leading to polarization and homophily.
Contribution
It introduces a novel bounded confidence model to estimate user internal sentiment and measures homophily in COVID-19 related discussions.
Findings
Topic volume aligns with external COVID-19 events.
Sentiment is influenced by previous posts, causing polarization.
Homophily measures indicate varying levels of sentiment clustering.
Abstract
This study investigates how topics and sentiments on COVID-19 mitigation measures -- specifically lockdowns, mask mandates, and vaccinations -- spread through the Belgian Reddit community. We explore 655,642 posts created between 1 January 2020 and 30 June 2022. In line with previous studies for other countries and platforms, we find that the volume of posts on these topics can be tied to important external events, but not within-Reddit interactions. Sentiment, however, is influenced by the sentiment of previous posts, resulting in homophily and polarisation. We define a homophily measure and find values of 0.228, 0.198, and 0.133 for lockdowns, masks and vaccination, respectively. Additionally, we introduce a novel bounded confidence model that estimates internal sentiment of users from their expressed sentiment. The Wasserstein metric between the predicted and the observed sentiments…
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Taxonomy
TopicsMisinformation and Its Impacts · Hate Speech and Cyberbullying Detection · Sentiment Analysis and Opinion Mining
