Identifying and Understanding User Reactions to Deceptive and Trusted Social News Sources
This work addresses the challenge of misinformation spread for social media users and platforms, but it is incremental as it applies existing methods to new data.
The study tackled the problem of understanding user reactions to trusted and deceptive news sources on social media by developing a model to classify reactions into nine types and analyzing 10.8M Twitter posts and 6.2M Reddit comments, finding significant differences in reaction speed and type on Twitter but smaller differences on Reddit.
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.