Identifying and Understanding User Reactions to Deceptive and Trusted Social News Sources

May 30, 2018 ยท Declared Dead ยท ๐Ÿ› Annual Meeting of the Association for Computational Linguistics

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Authors Maria Glenski, Tim Weninger, Svitlana Volkova arXiv ID 1805.12032 Category cs.CL: Computation & Language Citations 29 Venue Annual Meeting of the Association for Computational Linguistics Last Checked 4 months ago
Abstract
In the age of social news, it is important to understand the types of reactions that are evoked from news sources with various levels of credibility. In the present work we seek to better understand how users react to trusted and deceptive news sources across two popular, and very different, social media platforms. To that end, (1) we develop a model to classify user reactions into one of nine types, such as answer, elaboration, and question, etc, and (2) we measure the speed and the type of reaction for trusted and deceptive news sources for 10.8M Twitter posts and 6.2M Reddit comments. We show that there are significant differences in the speed and the type of reactions between trusted and deceptive news sources on Twitter, but far smaller differences on Reddit.
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