Constructing the Public Opinion Field: Media Materiality, Moral Economy, and Algorithmic Control in the Age of AI

Abstract

In the contemporary digital landscape, the construction of public opinion has become a complex interplay between media materiality, moral economy, and algorithmic control. Traditional media once mediated collective consciousness primarily through editorial gatekeeping and ideological frameworks, but with the emergence of artificial intelligence (AI), the mechanisms of influence have expanded and intensified. This paper examines how media infrastructures (platform architectures, networked devices, and data flows), moral economies (norms, values, and affective investments), and algorithmic systems (machine learning, personalization, and automated moderation) collectively shape the public opinion field. Drawing on interdisciplinary literature from media studies, political communication, and computational sociology, the study employs a mixed-methods approach: discourse analysis of media artifacts, survey-based exploration of public perception, and computational mapping of algorithmic recommendation patterns. Findings suggest that media materiality dictates the conditions of information circulation, algorithmic logics reinforce polarization and visibility hierarchies, and moral economies guide the reception and legitimacy of narratives. Together, these dynamics create a techno-social ecosystem where public opinion is less a spontaneous aggregation of individual voices than a managed field structured by infrastructures and automated governance. The paper concludes by highlighting ethical implications and proposing frameworks for democratic accountability in algorithmic governance.