Profiling Fake News Spreaders on Social Media through Psychological and Motivational Factors

TL;DR

This paper investigates the psychological and motivational traits of social media users who spread fake news, aiming to identify distinguishing features and improve detection methods based on behavioral analysis.

Contribution

It introduces a framework combining psychological theories with behavioral data to profile and detect fake news spreaders on social media.

Findings

Fake news spreaders exhibit distinct psychological traits.

Behavioral patterns can differentiate spreaders from regular users.

Proposed features improve fake news spreader detection accuracy.

Abstract

The rise of fake news in the past decade has brought with it a host of consequences, from swaying opinions on elections to generating uncertainty during a pandemic. A majority of methods developed to combat disinformation either focus on fake news content or malicious actors who generate it. However, the virality of fake news is largely dependent upon the users who propagate it. A deeper understanding of these users can contribute to the development of a framework for identifying users who are likely to spread fake news. In this work, we study the characteristics and motivational factors of fake news spreaders on social media with input from psychological theories and behavioral studies. We then perform a series of experiments to determine if fake news spreaders can be found to exhibit different characteristics than other users. Further, we investigate our findings by testing whether the characteristics we observe amongst fake news spreaders in our experiments can be applied to the detection of fake news spreaders in a real social media environment.