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Communities in Italian corporate networks

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Author Info

  • Piccardi, Carlo
  • Calatroni, Lisa
  • Bertoni, Fabio

Abstract

The community structure of two real-world financial networks, namely the board network and the ownership network of the firms of the Italian Stock Exchange, is analyzed by means of the maximum modularity approach. The main result is that both networks exhibit a strong community structure and, moreover, that the two structures overlap significantly. This is due to a number of reasons, including the existence of pyramidal groups and directors serving in several boards. Overall, this means that the “small world” of listed companies is actually split into well identifiable “continents” (i.e., the communities).

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Bibliographic Info

Article provided by Elsevier in its journal Physica A: Statistical Mechanics and its Applications.

Volume (Year): 389 (2010)
Issue (Month): 22 ()
Pages: 5247-5258

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Handle: RePEc:eee:phsmap:v:389:y:2010:i:22:p:5247-5258

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Web page: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/

Related research

Keywords: Networks; Communities; Modularity; Board network; Ownership network;

References

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Citations

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Cited by:
  1. Francesca Pallotti & Alessandro Lomi & Daniele Mascia, 2013. "From network ties to network structures: Exponential Random Graph Models of interorganizational relations," Quality & Quantity: International Journal of Methodology, Springer, Springer, vol. 47(3), pages 1665-1685, April.
  2. Wu, Jianshe & Li, Xiaoxiao & Jiao, Licheng & Wang, Xiaohua & Sun, Bo, 2013. "Minimum spanning trees for community detection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(9), pages 2265-2277.
  3. Shen, Yi, 2014. "The similarity of weights on edges and discovering of community structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 393(C), pages 560-570.
  4. Xiao-Qian Sun & Xue-Qi Cheng & Hua-Wei Shen & Zhao-Yang Wang, 2011. "Distinguishing manipulated stocks via trading network analysis," Papers 1110.2260, arXiv.org.
  5. Sun, Xiao-Qian & Cheng, Xue-Qi & Shen, Hua-Wei & Wang, Zhao-Yang, 2011. "Distinguishing manipulated stocks via trading network analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(20), pages 3427-3434.
  6. Stefania Vitali & Stefano Battiston, 2013. "The Community Structure of the Global Corporate Network," Papers 1301.2363, arXiv.org.

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