Facebook's Algorithms, Fake News, and Taiwan's 2018 Local Elections

This explorative study examines how Facebook's News Feed, fear of missing out (FOMO), news literacy, experience of fake news, disappointment at local election results, trust in the News Feed, and perceptions of algorithms affect users' attitude toward Facebook as a political news source and fake news regulations. After collecting 1453 valid online feedbacks, we find that the experiences of forwarding and receiving fake news play different roles. The experience of forwarding fake news raises trust in the News Feed and perceived risks of algorithmic biases (untruthfulness), while the experience of receiving fake news undermines trust and increases risk perceptions of algorithmic biases (both untruthfulness and decontexualisation). In addition, trust and risk perceptions of algorithmic biases significantly predict subjects' support for fake news regulations and preferred methods of such regulations. Lastly, FOMO, habitual usage, and tablet usage are evident predictors of fake news experiences and disappointment at the election results.