<![CDATA[Background: In digital ecosystems, individual information perception is mediated through social relationships, aligning with DeFleur’s Social Relationship Theory (SRT). Mass media messages are filtered by opinion leaders within social networks rather than affecting audiences linearly, as conceptualized by the hypodermic needle model. Social media algorithms further reinforce this dynamic, rendering interpersonal credibility more decisive for mass communication effectiveness than institutional media authority. Purpose: This study maps research trends on SRT regarding perception within mass communication, specifically examining how opinion leaders and algorithms disrupt linear message delivery, while identifying dominant thematic clusters via VOSviewer and exposing research gaps within communication studies. Method: Employing a Systematic Literature Review (LR) guided by PRISMA 2020 standards, this study analyzed Scopus-indexed journal articles published between 2015 and 2025. VOSviewer was utilized to process predetermined keywords and visualize inter-topic relationships. Results: The PRISMA screening narrowed 88,899 initial records to 327 articles, ultimately yielding only 8 studies directly situated within communication discipline, confirming a significant research gap. VOSviewer mapped four thematic "perception" clusters: sustainability management (red), clinical-demographics (green), psychology-education (yellow), and media stimulus-response (blue). A publication surge between 2018 and 2023 indicates that SRT has been adopted far more extensively by external disciplines than by its native field of communication studies. Conclusion: The core hypothesis of SRT that perception is socially mediated remains highly adaptive. The phenomenon of digital platformization now necessitates an extension of the theory to position algorithms and AI as algorithmic opinion leaders. Implications: This study equips communication scholars in regions with collectivist cultures, such as Indonesia, to analyze decentralized gatekeeping practices, AI-shaped public perceptions, and public acceptance of environmentally friendly policies.]]>
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