A Study of Partisan News Sharing in the Russian invasion of Ukraine
Yiming Zhu, Ehsan-Ul Haq, Gareth Tyson, Lik-Hang Lee, Yuyang Wang, Pan, Hui

TL;DR
This study analyzes how partisan news sharing during the Russian invasion of Ukraine influences online discussions on Reddit, revealing increased engagement but limited spread of biased media and identifying user characteristics related to partisan news dissemination.
Contribution
It provides a comprehensive measurement of partisan news sharing dynamics and introduces a predictive model for identifying users likely to spread partisan content.
Findings
Partisan news sharing increases during the invasion.
More biased media is less likely to be widely propagated.
Users spreading partisan news generate more comments but have lower network influence.
Abstract
Since the Russian invasion of Ukraine, a large volume of biased and partisan news has been spread via social media platforms. As this may lead to wider societal issues, we argue that understanding how partisan news sharing impacts users' communication is crucial for better governance of online communities. In this paper, we perform a measurement study of partisan news sharing. We aim to characterize the role of such sharing in influencing users' communications. Our analysis covers an eight-month dataset across six Reddit communities related to the Russian invasion. We first perform an analysis of the temporal evolution of partisan news sharing. We confirm that the invasion stimulates discussion in the observed communities, accompanied by an increased volume of partisan news sharing. Next, we characterize users' response to such sharing. We observe that partisan bias plays a role in…
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Taxonomy
TopicsOpinion Dynamics and Social Influence · Social Media and Politics · Complex Network Analysis Techniques
