The Network of French Legal Codes

We propose an analysis of the codified Law of France as a structured system. Fifty two legal codes are selected on the basis of explicit legal criteria and considered as vertices with their mutual quotations forming the edges in a network which properties are analyzed relying on graph theory. We find that a group of 10 codes are simultaneously the most citing and the most cited by other codes, and are also strongly connected together so forming a "rich club" sub-graph. Three other code communities are also found that somewhat partition the legal field is distinct thematic sub-domains. The legal interpretation of this partition is opening new untraditional lines of research. We also conjecture that many legal systems are forming such new kind of networks that share some properties in common with small worlds but are far denser. We propose to call "concentrated world".

Batch kernel SOM and related Laplacian methods for social network analysis

Large graphs are natural mathematical models for describing the structure of the data in a wide variety of fields, such as web mining, social networks, information retrieval, biological networks, etc. For all these applications, automatic tools are required to get a synthetic view of the graph and to reach a good understanding of the underlying problem. In particular, discovering groups of tightly connected vertices and understanding the relations between those groups is very important in practice. This paper shows how a kernel version of the batch Self Organizing Map can be used to achieve these goals via kernels derived from the Laplacian matrix of the graph, especially when it is used in conjunction with more classical methods based on the spectral analysis of the graph. The proposed method is used to explore the structure of a medieval social network modeled through a weighted graph that has been directly built from a large corpus of agrarian contracts.