What sells on the fake news market? Examining the impact of contextualized rhetorical features on the popularity of fake tweets

Abstract

A fake news ecosystem is akin to a marketplace where content generators and users exchange content like sellers and buyers. The popularity of a product in this marketplace is influenced by rhetorical features (ethos, pathos, and logos), topic categories (hard news, soft news, and general news), and design motivations (political intent, fun, etc.). Therefore, the determinants of the popularity of fake news should be contextualized better to understand the spreading patterns. First, we obtained a sample from a fact-checking organization (n=439). Then, we categorized tweets based on their topics and design motivation by using biaxial content analysis. Next, we proposed a rhetorical framework to organize the tweet-related indicators to develop the content’s systematic characterization. Finally, we examined both the primary and interaction effects of topics, design motivations, and organized rhetorical features of tweets on popularity through a negative binomial regression. The main results revealed a positive relationship between logos-related features (i.e., the number of followers) and the popularity of the fake tweets. In addition, an exciting interaction effect indicated that fake tweets designed with political intent are nearly five times less retweeted when they contain hashtags. The research and practical implications and future directions were also discussed.