Analyzing behavioral changes of Twitter users after exposure to misinformation

Yichen Wang, Richard O. Han, Tamara Lehman, Q. Lv, Shivakant Mishra
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引用次数: 3

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.
分析Twitter用户在接触错误信息后的行为变化
近年来,社交媒体平台被用来传播错误信息。广泛存在的网络错误信息已被证明会影响用户的信念,并与两极分化等社会影响有关。在这项工作中,我们专注于错误信息对特定用户行为的影响,旨在了解一般Twitter用户在接触错误信息后是否会改变他们的行为。我们比较了暴露用户的行为前后,以确定他们发布推文的频率,或者他们的推文情绪是否发生了重大变化。我们的结果表明,用户总体上在这些指标上表现出显著的行为变化。通过语言距离分析,我们发现暴露用户与暴露前的基线用户已经存在差异。我们还研究了两个特定用户群体的特征,即多重暴露和极端变化群体,这两个群体可能受到高度影响。最后,我们研究了用户在接触错误信息推文后的行为变化是否会随着关注者的数量或推文作者的关注者数量而变化,发现他们的行为变化都是相似的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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