Signal, Noise, and Burnout: A Human-Information Interaction Analysis of Voter Verification in a High-Volatility Environment
Kijung Lee

TL;DR
This study examines how high information volatility during the 2024 U.S. election affected citizens' ability to discern accurate news, revealing that fatigue and demographics, rather than platform type, influence verification challenges.
Contribution
It challenges platform-deterministic theories by showing that information fatigue and demographics, not social media reliance, drive verification difficulties during volatile periods.
Findings
No significant difference in verification difficulty between social media and mainstream news users.
Information fatigue and demographics significantly influence epistemic self-efficacy.
High volatility levels level the verification challenges across different information platforms.
Abstract
The 2024 U.S. Presidential Election unfolded within an information environment of unprecedented volatility, challenging citizens to navigate a torrent of rapidly evolving, often contradictory information while determining what to believe. This study investigates the cognitive mechanisms underlying epistemic self-efficacy - the perceived ability to distinguish accurate news from misinformation - across different information channels during this high-stakes election cycle. Drawing on data from the Pew Research Center's American Trends Panel (Wave 155, September 2024, N = 9,360), we test three hypotheses: (H1) whether reliance on social media predicts lower epistemic self-efficacy compared to mainstream news sources; (H2) whether perceived exposure to inaccurate information mediates this relationship; and (H3) whether information fatigue moderates the cognitive burden of verification…
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Taxonomy
TopicsMisinformation and Its Impacts · Social Media and Politics · Public Relations and Crisis Communication
