Emotions: The Unexplored Fuel of Fake News on Social Media

Abstract

ABSTRACT Easy access to equipment, software, and platforms to create, distribute, and provide access to fake news stories has exacerbated the problem of fake news, making for a large number of highly biased sources that are reaching the mainstream through social networks. The economics of emotion theory proposes that fake news headlines are created to evoke emotional responses in readers that will cause them to interact with the article in a way that allows the creator to make a profit (through clicking on the link to the full article, by sharing the article, etc.). This mixed methods study investigates the process by which individuals experience discrete emotional reactions to fake news headlines, and how these emotions contribute to the perpetuation of fake news through sharing behaviors. U.S. participants (n=879 across two waves) viewed one of eight false news headlines and reported their emotional reactions, belief in the headline, and potential sharing behaviors. In general, participants were more likely to believe headlines that aligned with their existing beliefs (e.g., liberals were more likely to believe negative news about conservatives), reacted with more negative emotions to headlines that attacked their party, and were more likely to report intentions to suppress (e.g., post a link to a fact check) fake news that attacked their own party. Emotional reactivity of participants was associated with response behavior intentions such that participants who reported high levels of emotions were more likely to take actions that would spread or suppress the fake news, participants who reported low levels of emotions were more likely to ignore or disengage from the spread of false news, and participants who reported high levels of negative emotions and low levels of positive emotions were more likely to suppress the spread of fake news and less likely to contribute to the spread of fake news. Our findings are synthesized into a process model that explains how discrete emotions and beliefs influence sharing behaviors. Implications for mitigating the spread of fake news are discussed in terms of this model.