Optimizing Digital Adjudication through Social Network Analysis: An Empirical Study of Credit Card Disputes in Beijing

TL;DR

This paper uses social network analysis to study credit card disputes in Beijing, revealing legal patterns and offering a data-driven approach to improve digital court systems' efficiency and consistency.

Contribution

It introduces a novel application of social network analysis to legal adjudication, uncovering structural legal patterns in digitalized judicial data.

Findings

SNA effectively identifies core legal norms.

Legal citation networks reveal case typologies.

Method enhances judicial data retrieval and consistency.

Abstract

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.