Network approach to the French system of legal codes part II: the role of the weights in a network

Original Research
  • 6 Downloads

Abstract

Unlike usual real graphs which have a low number of edges, we study here a dense network constructed from legal citations. This study is achieved on the simple graph and on the multiple graph associated to this legal network, this allows exploring the behavior of the network structural properties and communities by considering the weighted graph and see which additional information are provided by the weights. We propose new measures to assess the role of the weights in the network structure and to appreciate the weights repartition. Then we compare the communities obtained on the simple graph and on the weighted graph. We also extend to weighted networks the amphitheater-like representation (exposed in a previous work) of this legal network. Finally we evaluate the robustness of our measures and methods thus taking into account potential errors which may occur by getting data or building the network. Our methodology may open new perspectives in the analysis of weighted networks.

Keywords

Weighted network Structural measures Graph Legal code Codified legal system Communities 

References

  1. Boulet R, Mazzega P, Bourcier D (2011) A network approach to the French system of legal codes—part I: analysis of a dense network. Artif Intell Law 19(4):333–355Google Scholar
  2. Bourcier D, Mazzega P (2007) Codification, law article and graphs. In: Jurix AR, Lodder, Mommers L (eds) Legal knowledge and information systems. IOS Press, Amsterdam, pp 29–38Google Scholar
  3. Brandes U, Erlebach T (Eds) (2005), Network Analysis: Methodological Foundations. Lecture Notes in Computer Science, 3418Google Scholar
  4. Chung FRK (1997) Spectral Graph Theory, American Mathematical SocietyGoogle Scholar
  5. Clauset A, Newman MEJ, Moore C (2004) Finding community structure in very large networks. Phys Rev E 70:066111CrossRefGoogle Scholar
  6. Erdös P, Rényi A (1959) On random graphs. Publ Math 6:290–297MathSciNetMATHGoogle Scholar
  7. Fowler JH, Johnson TR, Spriggs JF II, Jeaon S, Wahlbeck PJ (2007) Network analysis and the law: measuring the legal importance of precedents at the U.S. Supreme Court. Political Anal 15(3):324–346CrossRefGoogle Scholar
  8. François, D (2013) Consolidation et codification, simplifier et faciliter l’accès au droit. Forum européen des journaux officielsGoogle Scholar
  9. Freeman LC (1979) Centrality in social networks: conceptual clarification. Soc Netw 1:215–239CrossRefGoogle Scholar
  10. Girvan M, Newman MEJ (2002) Community structure in social and biological networks. Proc Natl Acad Sci USA 99:7821–7826MathSciNetCrossRefMATHGoogle Scholar
  11. Grossman JW (2002) The evolution of the mathematical research collaboration graph. Congr Numer 158:202–212MathSciNetMATHGoogle Scholar
  12. Jouve B, Kuntz P, Velin F (2002) Extraction de structures macroscopiques dans des grands graphes par une apporche spectrale. Extraction des Connaissances et Apprentissage 1:173–184Google Scholar
  13. Katz DM, Bommarito M (2014) Measuring the Complexity of the Law: the United States Code. J Artif Intell Law 22(4):337–374CrossRefGoogle Scholar
  14. Latapy M, Magnien C (2006) Measuring Fundamental Properties of Real-World Complex Networks”, http://arxiv.org/abs/cs.NI/0609115
  15. Mazzega P, Bourcier D, Boulet R (2009a) The Network of French Legal Codes. Proc ICAIL. doi:10.1145/1568234.1568271 Google Scholar
  16. Mazzega P, Bourcier D, Boulet R (2009b) Code Communities in the French Legal System. In: Proceedings of GEMME 2009Google Scholar
  17. Newman MEJ (2004) Fast algorithm for detecting community structure in networks. Phys Rev E 69:066133CrossRefGoogle Scholar
  18. Pons P, Latapy M (2005) Computing communities in large networks using random walks. J Graph Algorithms Appl 10:191–218MathSciNetCrossRefMATHGoogle Scholar
  19. Schuck PH (1992) Legal complexity: some causes, consequences, and cures. Duke L J 42(1):1–52MathSciNetCrossRefGoogle Scholar
  20. Tarissan F, Nollez Goldbach R (2015) Temporal properties of legal decision networks: a case study from the International Criminal Court, In: 28th International conference on legal knowledge and information systems (JURIX’2015), Braga, PortugalGoogle Scholar
  21. von Luxburg U (2007) A Tutorial on Spectral Clustering. Stat Comput 17:395–416MathSciNetCrossRefGoogle Scholar
  22. Watts DJ (2003) Small worlds: the dynamics of networks between order and randomness. Princeton University Press, PrincetonMATHGoogle Scholar
  23. Watts DJ, Strogatz SH (1998) Collective dynamics of ‘small-world’ networks. Nature 393:440–442CrossRefGoogle Scholar
  24. Whalen R (2016) Legal networks: the promises and challenges of legal network analysis. Mich. St. L Rev, Michigan, p 539Google Scholar
  25. Winkels RGF, Boer A (2014) Finding and visualizing dutch legislative context networks. In: Winkels R, Lettieri N, Faro S (eds) Network analysis in law. Diritto Scienza Tecnologia, Rome, pp 157–182Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2017

Authors and Affiliations

  • Romain Boulet
    • 1
  • Pierre Mazzega
    • 2
  • Danièle Bourcier
    • 3
  1. 1.Univ. Lyon, Jean Moulin, iaelyon, Magellan Research CenterLyonFrance
  2. 2.UMR5563 Geosciences Environment Toulouse, CNRS, University of ToulouseToulouseFrance
  3. 3.CERSA CNRS, Université de Paris 2ParisFrance

Personalised recommendations