DIGITAL GATEKEEPING: HOW ALGORITHMS SHAPE NEWS EXPOSURE AND PUBLIC OPINION IN THE GLOBAL SOUTH

Abstract

This study examines how algorithmic gatekeeping shapes news exposure and public opinion in the Global South, where digital platforms increasingly serve as primary sources of information. Drawing on Gatekeeping Theory, Algorithmic Gatekeeping Theory, and Agenda-Setting Theory, the research investigates relationships among algorithmic news exposure, trust, digital literacy, awareness of personalization, and public opinion formation. A cross-sectional survey of 1,200 participants from Pakistan, India, and Bangladesh was conducted, and data were analyzed using descriptive statistics, multiple regression, and Structural Equation Modeling (SEM). Findings reveal that algorithmic recommendation systems significantly influence patterns of news consumption, issue salience, and opinion formation. Participants reported high reliance on platform-curated content yet demonstrated low levels of awareness regarding algorithmic filtering. Algorithmic exposure strongly predicted opinion formation, with trust and issue salience mediating the relationship. Digital literacy moderated algorithmic influence, indicating that users with greater understanding were less affected by automated curation. Younger and digitally active respondents demonstrated higher trust in algorithmically recommended news. The study highlights critical implications for democratic communication in the Global South, where weak media regulation, low literacy, and political instability increase vulnerability to algorithmic manipulation. Results underscore the need for transparency in platform governance, stronger media literacy interventions, and policy frameworks addressing algorithmic accountability. The findings advance scholarly understanding of digital power structures and emphasize the importance of contextual research beyond Western-dominated perspectives.