Quantifying the Influence of User Behaviors on the Dissemination of Fake News on Twitter with Multivariate Hawkes Processes

TL;DR

This paper introduces a multivariate Hawkes process model to quantify how user behaviors, such as network connections and tweet types, influence the spread of fake news on Twitter, aiding in intervention strategies.

Contribution

It develops a novel multivariate Hawkes model incorporating user stance and tweet type factors, with parameter estimation via EM algorithm, validated on real Twitter fake news data.

Findings

User stances significantly affect dissemination patterns

Tweet types influence the speed of fake news spread

Model provides insights for intervention strategies

Abstract

Fake news has emerged as a pervasive problem within Online Social Networks, leading to a surge of research interest in this area. Understanding the dissemination mechanisms of fake news is crucial in comprehending the propagation of disinformation/misinformation and its impact on users in Online Social Networks. This knowledge can facilitate the development of interventions to curtail the spread of false information and inform affected users to remain vigilant against fraudulent/malicious content. In this paper, we specifically target the Twitter platform and propose a Multivariate Hawkes Point Processes model that incorporates essential factors such as user networks, response tweet types, and user stances as model parameters. Our objective is to investigate and quantify their influence on the dissemination process of fake news. We derive parameter estimation expressions using an Expectation Maximization algorithm and validate them on a simulated dataset. Furthermore, we conduct a case study using a real dataset of fake news collected from Twitter to explore the impact of user stances and tweet types on dissemination patterns. This analysis provides valuable insights into how users are influenced by or influence the dissemination process of disinformation/misinformation, and demonstrates how our model can aid in intervening in this process.