  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 narrowing its propagation. More biased media is
less likely to be spread across multiple subreddits. However, we find that
partisan news sharing attracts more users to engage in the discussion, by
generating more comments. We then built a predictive model to identify users
likely to spread partisan news. The prediction is challenging though, with
61.57% accuracy on average. Our centrality analysis on the commenting network
further indicates that the users who disseminate partisan news possess lower
network influence in comparison to those who propagate neutral news.
