Optimizing Digital Adjudication through Social Network Analysis: An Empirical Study of Credit Card Disputes in Beijing
It addresses the underexplored integration of big data in judicial systems, specifically for credit card disputes in Beijing, offering practical pathways for enhancing efficiency and consistency, but it is incremental as it applies an existing method to a new domain.
This study tackled the problem of integrating big data into judicial systems by using social network analysis to examine credit card disputes in Beijing, revealing latent patterns in legal application and demonstrating that SNA can identify core norms and typify cases to optimize digital court systems.
Amid the rapid digitalization of judicial systems, the integration of big data into adjudication remains underexplored, particularly in uncovering the structural logic of legal applications. This study bridges this gap by employing social network analysis (SNA) to examine credit card disputes involving personal information protection adjudicated in Beijing. By constructing a legal citation network, we reveal the latent patterns of substantive and procedural law application. The findings demonstrate that SNA can effectively identify core legal norms and typify cases, offering a robust methodological framework for optimizing 'Digital Court' systems. These insights provide practical pathways for enhancing judicial efficiency and consistency through data-driven case retrieval and holistic judicial information networks.