Layered community-aware layout method for complex statute network visualization

A country’s statutes (laws) are the foundation of its legal system. The statutes are connected to each other through citations, forming a complex, hierarchical network. While there have been efforts to analyze the network properties of the statute networks of some countries, the fact that a country’s law touches every aspect of the residents of a country suggests that there further exist multiple worthy avenues to pursue from complex network and data science. Developments in those areas can be of help not only to the legal professionals but also to the general public in understanding and making use of the laws. One such avenue would be an effective visualization technique for the statute network that reveals its structural features for practical exploration and navigability. Here, we propose the Layered Community-Aware Layout (LCGraph) visualization technique. LCGraph detects densely connected communities through recursive clustering and then minimizes community overlaps and edge crossings to reveal the network’s structure. We apply our method to the complete statute network of the Republic of Korea, then compare it with a number of other methods through a set of quantitative parameters and a user study. We show that LCGraph outperforms the others by achieving an effective balance between aesthetic clarity, community cohesion, and the preservation of both local and global structures, indicating suitability for statutes from many jurisdictions.