Algorithmic Audiences: Navigating Identity, Influence, and Power in the Age of Platformized Media

Purpose: This article investigates the formation and operation of algorithmic audiences within platformized media environments, focusing on how processes of identity, influence, and power intersect to shape audience behaviour. It seeks to theorise the algorithmically produced publics that emerge from data-driven engagement on social media, streaming services, and online gaming platforms. Methods: The study employs a critical conceptual synthesis of current literature in media studies, platform capitalism, and communication theory, supported by illustrative case studies of user-platform interactions. Through thematic analysis of secondary sources (2017–2023), it maps how algorithmic recommendation systems, identity performances, and influence mechanisms mutually reinforce each other to establish dynamic audience configurations. Results: Findings reveal that algorithmic audiences are neither passive recipients nor purely autonomous actors, but datafied hybrid entities produced through collaborative interplays of user self-presentation, platform logics, and commercial surveillance. Identity construction increasingly depends on visibility metrics, while influence is redistributed through opaque recommendation architectures producing echo chambers and filter bubbles. Power asymmetries deepen as platforms gain control over information flows, data extraction, and behavioural manipulation, raising serious ethical and regulatory concerns. Conclusion: Algorithmic audiences represent a paradigm shift in the understanding of contemporary media publics. Their emergence compels scholars and policymakers to move beyond traditional audience theories and to confront new questions surrounding data ownership, platform governance, and audience agency in the age of automated curation. Future research must address how regulatory frameworks and ethical design interventions can protect user autonomy while ensuring transparency and accountability within platformised media ecosystems.