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The news ecosystem has become increasingly complex, encompassing a wide rangeof sources with varying levels of trustworthiness, and with public commentarygiving different spins to the same stories. In this paper, we present amulti-platform measurement of this ecosystem. We compile a list of 1,073 newswebsites and extract posts from four Web communities (Twitter, Reddit, 4chan,and Gab) that contain URLs from these sources. This yields a dataset of 38Mposts containing 15M news URLs, spanning almost three years.  We study the data along several axes, assessing the trustworthiness of sharednews, designing a method to group news articles into stories, analyzing thesestories are discussed and measuring the influence various Web communities havein that. Our analysis shows that different communities discuss different typesof news, with polarized communities like Gab and /r/The_Donald subredditdisproportionately referencing untrustworthy sources. We also find that fringecommunities often have a disproportionate influence on other platforms w.r.t.pushing narratives around certain news, for example about political elections,immigration, or foreign policy.

A Multi-Platform Analysis of Political News Discussion and Sharing on Web Communities