Abstract: Earthquake disaster scenario construction constitutes a critical technological approach for enhancing earthquake prevention and disaster mitigation capabilities. However, its precision and timeliness remain constrained by the limitations of traditional data sources. This study systematically examined the enabling mechanisms of social data in earthquake disaster scenario construction, focusing on the characteristics of comprehensiveness, dynamism, and diversity. A hierarchical classification framework for social data is proposed by mapping the data requirements for scenario construction. Case studies integrating Zhejiang’s public data platforms, social media dynamics, and commercial remote-sensing data demonstrate that multi-source data fusion significantly improves scenario authenticity, refinement, and dynamic adaptability. The research reveals that social data effectively compensate for coverage gaps in traditional data sources, substantially strengthening the scientific validity of disaster prediction, resource allocation, and public response mechanisms. Building on these findings, the study proposes institutional innovations for data sharing, technological integration pathways, and policy recommendations, providing theoretical and practical foundations for advancing earthquake disaster scenario construction toward a “physical-social” modeling paradigm.