The Historical Evolution of Public Trust in Media: A Comparative Diachronic Study of Print, TV, and AI Using Structural Equations and Content Analysis

Abstract

This study explores the diachronic evolution of media credibility mechanisms, transitioning from the institutional authority of the print era to the charismatic presence of television, and ultimately to the algorithmic logic of Artificial Intelligence. While traditional scholarship often addresses media trust crises as isolated phenomena, this research adopts an integrated structural approach. Utilizing a dual methodology that combines quantitative content analysis with Structural Equation Modeling (SEM), the study identifies three distinct discursive models of trust. The findings demonstrate a fundamental shift in the "epistemology of certainty": from a model anchored in professional gatekeeping and institutional mastheads, through a sensory-emotional paradigm centered on the news anchor, to a contemporary data-centric model. In this final stage, inferred trust is no longer constructed through human authority but through perceived algorithmic transparency and the computational verifiability of data. The research highlights the structural fragility of this new paradigm, where the burden of credibility shifts from personal expertise to technological transparency.