Truth and the Dynamics of News Diffusion on Twitter

Abstract

This chapter investigates two aspects of misinformation: how to determine whether information (such as a news story) is true, and how the truthfulness of information affects its diffusion or spread. The chapter has a particular focus on the significance of social media for misinformation (in particular fake news): its prevalence, impact, and methods for identifying and studying the phenomenon. We review recent literature on how computational methods and “big data” sources (e.g., social media) are being used for identifying misinformation and understanding how people engage with and spread misinformation. Our empirical application involves a new approach for manually checking the truthfulness of news stories, and we apply this method to a sample of Australian political news stories from 2017. We then explore how the veracity of news affects its diffusion (via retweets) on Twitter, focusing on the following key measures of diffusion: reach (how many people are involved in the diffusion), speed, and breadth (how far into the network does the news spread, and how diverse are the actors involved in the diffusion).