Social media have become a central medium for social interaction, information seeking, leisure activities, and self-presentation. While SNS use is an integral part of everyday life for most users, some experience excessive use that exceeds self-regula...
Social media have become a central medium for social interaction, information seeking, leisure activities, and self-presentation. While SNS use is an integral part of everyday life for most users, some experience excessive use that exceeds self-regulatory control and negatively affects daily functioning and interpersonal relationships, a phenomenon referred to as SNS overdependence. Previous research has often used concepts such as addiction, problematic use, and excessive use interchangeably, failing to clearly distinguish clinical addiction from overdependence occurring in everyday contexts. To address this limitation, this study conceptualizes SNS overdependence as a non-clinical yet intensified form of excessive SNS use and focuses on its key psychological correlates: multidimensional loneliness (emotional, relational, and collective), fear of missing out (FoMO), and SNS self-presentation strategies. This study pursues three objectives. First, it identifies latent profiles among Korean SNS users aged 14–59 based on combinations of loneliness dimensions and trait FoMO. Second, it compares differences in positive self-presentation, honest self-presentation, and SNS overdependence across these profiles. Third, it examines indirect pathways from FoMO–loneliness profiles to SNS overdependence via self-presentation strategies using structural equation modeling, treating latent profiles as exogenous categorical variables. An online survey was conducted with 1,172 Korean SNS users recruited through a professional panel. Measures included trait FoMO, emotional, relational, and collective loneliness, positive and honest self-presentation, and SNS overdependence. Latent profile analysis (LPA) was performed, followed by group comparisons using the Bolck–Croon–Hagenaars (BCH) three-step method and mediation analysis via structural equation modeling. Four latent profiles emerged: a low FoMO–low loneliness group, a low FoMO–moderate loneliness group, a moderate FoMO–high loneliness group, and a high FoMO–emotional loneliness group. The low FoMO–low loneliness group represented a low-risk profile, whereas the high FoMO–emotional loneliness group exhibited pronounced emotional loneliness and elevated FoMO, indicating high risk. Overall, higher levels of FoMO and loneliness were associated with greater engagement in both positive and honest self-presentation and with higher SNS overdependence. In particular, the moderate FoMO–high loneliness and high FoMO–emotional loneliness groups showed significantly higher levels of self-presentation and SNS overdependence than the low-risk group. By contrast, the low FoMO–moderate loneliness group displayed relatively low FoMO and personal loneliness but higher collective loneliness, suggesting a distinct SNS use pattern. Mediation analyses further revealed that positive and honest self-presentation partially mediated the relationship between latent profiles and SNS overdependence in specific groups, with these pathways being especially pronounced in the moderate FoMO–high loneliness and high FoMO–emotional loneliness profiles. These findings indicate that, among psychologically vulnerable users, self-presentation aimed at seeking emotional support and social recognition may paradoxically intensify SNS overdependence. In conclusion, this study provides a profile-level understanding of the relationship between FoMO, multidimensional loneliness, and SNS overdependence through a latent profile approach that extends beyond traditional variable-centered research. By conceptualizing positive and honest self-presentation as coexisting strategies and demonstrating their profile-specific mediating roles, the findings identify self-presentation as a key mechanism through which psychological vulnerability is translated into behavioral overdependence in digital environments. The results also offer practical implications for identifying at-risk groups and developing tailored interventions, digital well-being education, counseling strategies, and platform design.