Patterns, Models, and Challenges in Online Social Media: A Survey

The rise of digital platforms has enabled the large-scale observation of individual and collective behavior through high-resolution interaction data. This development has opened new analytical pathways for investigating how information circulates, how opinions evolve, and how coordination emerges in online environments. Yet despite a growing body of research, the field remains fragmented, marked by methodological heterogeneity, limited model validation, and weak integration across domains. In this survey, we address this gap by systematically reviewing the literature on online collective behavior, integrating empirical findings with formal modeling approaches. We examine platform-level regularities, the methodological choices used to identify them, and the extent to which existing modeling frameworks capture the observed dynamics. Rather than aiming for exhaustive coverage of individual subfields, we provide a structural and comparative synthesis of recurring empirical patterns, methodological approaches, and modeling assumptions that span across platforms and domains. The overarching goal is to consolidate a shared empirical baseline and to clarify the structural constraints shaping inference in this area, thereby laying the groundwork for more robust, comparable, and actionable analyses of online social media.