07/06/2020

Characterizing the Social Media News Sphere through User Co-Sharing Practices

Mattia Samory, Vartan Kesiz Abnousi, Tanushree Mitra

Keywords: articles, communities, groups, linguistic, measures, misinformation, news, news articles, news sources, political, shared, sources, structure, twitter

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Abstract: We describe the landscape of news sources which share social media audience. We focus on 639 news sources, both credible and questionable, and characterize them according to the audience that shares their articles on Twitter. Based on user co-sharing practices, what communities of news sources emerge? We find four groups: one is home to mainstream, high-circulation sources from all sides of the political spectrum; one to satirical, left-leaning sources; one to bipartisan conspiratorial, pseudo-scientific sources; and one to right-leaning, deliberate misinformation sources. Next, we measure which assessments of credibility, impartiality, and journalistic integrity correspond to social media readers’ choices of news sources, and uncover the multifaceted structure of the social news sphere. We show how news articles shared on Twitter differ across the four groups along linguistic and psycholinguistics measures. Further, we find that with a high degree of accuracy (~80%), we can classify in what news community an article belongs to. Our data-driven categorization of news sources will help to navigate the complex landscape of online news and has implications for social media platforms as well as for journalism scholars.

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