

Author: Chapanond Anurat Krishnamoorthy Mukkai Yener Bülent
Publisher: Springer Publishing Company
ISSN: 1381-298X
Source: Computational & Mathematical Organization Theory, Vol.11, Iss.3, 2005-10, pp. : 265-281
Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.
Abstract
Analysis of social networks to identify communities and model their evolution has been an active area of recent research. This paper analyzes the Enron email data set to discover structures within the organization. The analysis is based on constructing an email graph and studying its properties with both graph theoretical and spectral analysis techniques. The graph theoretical analysis includes the computation of several graph metrics such as degree distribution, average distance ratio, clustering coefficient and compactness over the email graph. The spectral analysis shows that the email adjacency matrix has a rank-2 approximation. It is shown that preprocessing of data has significant impact on the results, thus a standard form is needed for establishing a benchmark data.
Related content


Structure in the Enron Email Dataset
Computational & Mathematical Organization Theory, Vol. 11, Iss. 3, 2005-10 ,pp. :


By Diesner Jana Frantz Terrill Carley Kathleen
Computational & Mathematical Organization Theory, Vol. 11, Iss. 3, 2005-10 ,pp. :



