<![CDATA[This study aims to map the development and direction of research on self-disclosure in social media from 2020 to 2025, using a bibliometric approach. Self-disclosure is a crucial communication process in the formation and maintenance of interpersonal relationships, which in the digital context has undergone significant transformation due to the presence of an unlimited audience, algorithm dynamics, and the technical characteristics of social platforms. This study utilises data from Dimensions and visualises the literature structure using VOS Viewer software, which includes four main types of analysis: publication trend analysis, keyword co-occurrence, co-authorship, and co-citation. The analysis results indicate that dominant themes in self-disclosure research include the influence of digital platforms, the role of algorithms, and the implications of disclosure intent and impact. Additionally, scientific collaboration remains fragmented and citation connections tend to follow thematic patterns. This study also identifies theoretical and methodological gaps, particularly in interdisciplinary approaches and geographical representation, highlighting the need for communication-centered theoretical integration. These findings underscore the urgency of updating theory, integrating cross-disciplinary approaches, and expanding the research context to understand self-disclosure practices amid the ever-changing social media landscape. Keywords: bibliometrics; digital platforms; research trends; self-disclosure; social media]]>
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