Fake News Framing, Emotion, Argumentation, and Dialogic Social Knowledge Building in Online Discussions: An Exploration Including Natural Language Processing Data

Abstract

Fake news negatively impacts individuals and society by bringing misinformation and negative emotions into the social knowledge building process, affecting reasoning and argumentation, and leading to misconceptions. Semantic, emotional, and value framing are frequent instruments of fake news dissemination; however, little is known about their effects. In this study, we investigate to what extent fake news framing predicts emotions, argumentation, and social knowledge building in online discussions at a German site. Employing manual content analysis of postings, and automated content analysis of online discussions based on natural language processing, we found significant relationships. Prominently, fake news framing predicted a large amount of variance in two indicators of social knowledge building. Our findings may inform fake news literacy interventions that counteract fake news by making framing transparent to the news consumers.