THE ROLE OF ARTIFICIAL INTELLIGENCE IN AUDIENCE-CENTRIC MEDIA TYPOLOGY: PERSONALIZED CONTENT, ALGORITHMIC SEGMENTATION, AND BEHAVIORAL ANALYTICS

This study examines the transition of media from the traditional production-centered communication model to an audience-centered media ecosystem driven by data and artificial intelligence from theoretical and analytical perspectives. The study demonstrates that digitalization and platformization have transformed audiences from passive recipients into measurable, predictable, and algorithmically guided analytical subjects. Behavioral analytics, personalized content, dynamic segmentation, and recommendation systems have fundamentally transformed the mechanisms of media production, distribution, and agenda-setting, transferring certain editorial decisions to algorithmic models. At the same time, this transformation raises fundamental ethical and normative concerns related to privacy, algorithmic bias, transparency, and editorial responsibility. Ultimately, the study argues that artificial intelligence in media should be understood not merely as a technological innovation but as an epistemological and institutional transformation that reshapes the concept of the audience, the public role of journalism, and the structure of the democratic information environment.