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

Authors

  • Chung Han Tsai School of Business Administration, Guangzhou Institute of Science and Technology, Guangzhou, China, 510540 Author
  • ChengTo Lin Renmin University of China, Beijing, China, 100044 Author
  • Baowen Zhang Renmin University of China, Beijing, China, 100044 Author
  • Qingyue Deng ShanDong University, Shandong, China, 266237 Author
  • Yunhui Zhao ShanDong University, Shandong, China, 266237 Author
  • Zhijia Song ShanDong University, Shandong, China, 266237 Author

DOI:

https://doi.org/10.71465/fbf572

Keywords:

Judicial Cognition, Digital Court, Social Network Analysis (SNA), Legal Reasoning Network, Computational Legal Studies

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 (2022–2024). 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.

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Published

2026-01-08