Algorithmic skepticism and user trust in social media platforms amid ideological differences
Published: August 10, 2026
Abstract
This study examines how perceived ideological differences between users’ home countries and the countries of origin of social media platforms influence algorithmic skepticism and data-sharing intentions. Drawing on Social Exchange Theory and Privacy Calculus Theory, data from 350 Generation Z and Millennial users in Vietnam were analyzed using PLS-SEM. The results show that perceived ideological differences significantly increase algorithmic skepticism, which heightens privacy concerns and reduces platform trust. Although perceived algorithmic convenience strengthens trust, privacy concerns remain the strongest barrier, directly and indirectly reducing users’ willingness to share personal data. The findings extend research on the privacy paradox by incorporating geopolitical and ideological considerations and provide implications for transparent algorithm governance, responsible data practices, cross-border platform management, and digital policymaking.
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