User-Reported Misinformation Exposure Across Social Media Platforms

πŸ“… 2026-07-28
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πŸ€– AI Summary
This study investigates differences in users’ subjective perceptions of misinformation exposure across distinct types of social media platforms and the factors underlying these variations. Through a large-scale survey of 1,010 U.S. residents and subsequent statistical analysis, it systematically compares perceived exposure across discovery-oriented, interpersonal, and discussion-based platforms for the first time. The findings reveal significant inter-platform differences in perceived misinformation exposure, primarily driven by public information feeds rather than content from known contacts, and show only a moderate correlation between perceived exposure and platform usage frequency. Building on a functional classification of platforms, this work proposes a differentiated governance framework for misinformation, offering a theoretically grounded basis for targeted policy interventions.
πŸ“ Abstract
In this study, we surveyed users for their perception of misinformation exposure across social media platforms. Such perceived exposure is important because individuals' beliefs about how often they encounter false information can shape their trust in institutions, platforms, and even their friends. In a survey of 1,010 United States residents, we found that perceived exposure to misinformation varies substantially across platforms and is only moderately correlated with the frequency of platform use. A much larger percentage of participants also reported being exposed to misinformation from the public feed than from known contacts. Based on these results, we propose governance strategies across three categories of platform types: discovery, interpersonal, and discourse. This work offers insight into users' perceptions of social media misinformation and a corresponding research agenda for governance.
Problem

Research questions and friction points this paper is trying to address.

misinformation exposure
social media platforms
user perception
platform governance
false information
Innovation

Methods, ideas, or system contributions that make the work stand out.

misinformation exposure
user perception
platform governance
social media types
public feed
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