Identifying Community Structures from Network Data
نویسندگان
چکیده
We describe, axiomatize, and implement, a new method for identifying community structures (groups of structurally equivalent nodes) from network data. The method is based on maximum likelihood estimation, a standard statistical tool. μ Copiμc and Jackson are at the Division of the Humanities and Social Sciences, California Institute of Technology, Pasadena, California 91125, USA, emails: [email protected] and [email protected], web sites: http://www.hss.caltech.edu/ jacksonm/Jackson.html and http://www.hss.caltech.edu/ copic. Kirman is at GREQAM, Université de la Mediterranée, 2 rue de la Charité, 13236 Marseille CEDEX 02, France, email: [email protected] . We gratefully acknowledge nancial support under NSF grant SES-0316493, as well as from the Lee Center for Advanced Networking and the Social Information Sciences Laboratory at Caltech. We thank Matteo Marsili for helpful conversations and Rik Pieters and Hans Baumgartner for making their data available.
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