Document Type : .
Authors
1
Ph.D. Candidate in Media Management, University of Tehran,(Tehran, Iran)
2
Assistant Professor, Department of Media Management and Business Communication, Faculty of Business Management, College of Management, University of Tehran, Tehran, Iran
10.30465/ismc.2026.53131.2993
Abstract
This study examines the layered construction and future transformation of audience identity in social media environments. Drawing on Causal Layered Analysis (CLA), the research moves beyond surface-level descriptions of user profiles and investigates how audience identity is reproduced through the interaction of datafication, platform algorithms, cultural discourses, and deep social metaphors. The study is based on a qualitative-interpretive design, including the analysis of 60 public Persian-language profiles on Instagram, X, and TikTok, semi-structured interviews with 15 users and content creators, and platform-related documents concerning visibility, recommendation systems, privacy, advertising, and community rules. The findings reveal that audience identity in social media is neither purely individualized nor entirely collective-networked. Rather, it is formed through a dynamic layered configuration in which users are individualized at the level of data and algorithms, while the meaning of identity continues to be produced through collective narratives, networked belonging, and cultural imaginaries. The most analytically coherent future scenario identified by the study is therefore a hybrid-layered scenario in which individual branding and collective-networked identity coexist in tension. The study contributes to media and communication theory by demonstrating how CLA can reveal the hidden causal relations between profile data, algorithmic structures, identity discourses, and cultural myths.
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