Analyzing Behavioral Changes of Twitter Users After Exposure to Misinformation

TL;DR

This study investigates how exposure to misinformation on Twitter influences user behavior, revealing significant behavioral shifts and pre-existing differences among exposed users, with minimal variation based on follower counts.

Contribution

It provides a detailed analysis of behavioral changes post-misinformation exposure and identifies pre-existing differences among affected users, which was not extensively studied before.

Findings

Users showed statistically significant behavioral changes after exposure.

Exposed users were already different from baseline users before exposure.

Behavioral changes were consistent regardless of follower counts.

Abstract

Social media platforms have been exploited to disseminate misinformation in recent years. The widespread online misinformation has been shown to affect users' beliefs and is connected to social impact such as polarization. In this work, we focus on misinformation's impact on specific user behavior and aim to understand whether general Twitter users changed their behavior after being exposed to misinformation. We compare the before and after behavior of exposed users to determine whether the frequency of the tweets they posted, or the sentiment of their tweets underwent any significant change. Our results indicate that users overall exhibited statistically significant changes in behavior across some of these metrics. Through language distance analysis, we show that exposed users were already different from baseline users before the exposure. We also study the characteristics of two specific user groups, multi-exposure and extreme change groups, which were potentially highly impacted. Finally, we study if the changes in the behavior of the users after exposure to misinformation tweets vary based on the number of their followers or the number of followers of the tweet authors, and find that their behavioral changes are all similar.