In the context of rapidly evolving digital media ecosystems, how can traditional theoretical frameworks in Mass Communication such as Agenda-Setting or Uses and Gratifications, be adapted to analyze audience behavior on algorithm-driven platforms like TikTok or Instagram Reels? With algorithms acting as new gatekeepers and user experiences shaped by personalization and data-driven content delivery, are classical theories sufficient, or should we move toward more integrative, digitally responsive models?
The accelerating integration of datafication (the transformation of social action into quantifiable data) and algorithmic influence (the shaping of human behavior through algorithmic systems) raises profound theoretical challenges. These forces are reshaping power structures, agency, and meaning in ways that many traditional frameworks only partially address. While existing models from media theory, sociology, and critical theory still hold value, there’s a strong argument for a new hybrid theoretical framework—one that fully integrates the nuances of our datafied and algorithmically mediated world.
Why Existing Models Are Under Strain
Classical theories like Agenda-Setting and Uses and Gratifications still offer value but need updating for algorithm-driven platforms. Algorithms now shape content and user behavior, acting as new gatekeepers. We need hybrid models that blend traditional theory with data-driven insights to understand its uses.
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