ALGORITHMIC NEWS CURATION, MISINFORMATION EXPOSURE, AND PUBLIC TRUST: A STUDY OF DIGITAL MEDIA CONSUMPTION IN PAKISTAN

Abstract

The rapid integration of algorithmic systems into digital media platforms has transformed news consumption patterns, raising critical concerns regarding misinformation exposure and public trust. This study examined the relationship between algorithmic news curation, misinformation exposure, and public trust in the context of Pakistan’s evolving digital media landscape. A quantitative research design was employed using a cross-sectional survey of 400 digital media users. Data were analyzed through descriptive statistics, correlation, regression, mediation, and moderation analyses.The findings revealed that algorithmic news curation significantly increases users’ exposure to misinformation, which in turn negatively affects public trust in digital news sources. Additionally, algorithmic curation demonstrated a direct negative impact on trust, highlighting concerns related to transparency and perceived bias in automated systems. The study further established that misinformation exposure mediates the relationship between algorithmic curation and public trust, while perceived credibility of algorithms moderates the strength of this relationship.The study concludes that although algorithmic systems enhance access to information, they also contribute to information disorder and declining trust in media. The findings underscore the need for improved algorithmic transparency, stronger misinformation control mechanisms, and enhanced media literacy initiatives in Pakistan. This research contributes to the theoretical understanding of algorithmic gatekeeping and provides practical insights for policymakers, media organizations, and digital platforms.