TWITTER/X'S PAID VERIFICATION SYSTEM: EFFECTS ON SOURCE CREDIBILITY AND DISINFORMATION SPREAD DURING THE 2025 GLOBAL HEALTH ALERTS

Abstract
The transition of Twitter's verification system from a credibility-based authentication mechanism to a paid subscription model represents a critical juncture in the evolution of social media governance, with profound implications for public health communication. This study examines the effects of X's (formerly Twitter) paid verification system on source credibility assessments and disinformation dissemination during the 2025 global health alerts, including Sudan virus disease outbreaks in East Africa, Marburg virus cases in Tanzania, and human metapneumovirus (HMPV) concerns across the African continent. Employing a mixed-methods approach combining experimental survey data, content analysis, and case study methodology, the research investigates how the commodification of verification badges has transformed the information ecosystem surrounding health emergencies. Findings indicate that verification badges no longer function as reliable heuristics for credibility assessment, with experimental data demonstrating null effects on users' accuracy perceptions (Neely & Witkowski, 2024). Concurrently, empirical evidence reveals that verified accounts constitute 88% of misleading health-related posts on X, while platform-mandated fact-checking mechanisms reach only 1% of viral misinformation (Center for Countering Digital Hate, 2025). The study identifies three interconnected mechanisms driving this phenomenon: the breakdown of verification as a credibility signal, algorithmic amplification of engagement-driven content regardless of accuracy, and the failure of crowdsourced fact-checking systems during acute health emergencies. These findings contribute to theoretical understandings of digital credibility heuristics, information disorder, and platform governance, while offering practical recommendations for health communication professionals, policymakers, and platform designers seeking to mitigate the public health impacts of misinformation during global health crises.