Graph Theoretic and Spectral Analysis of Enron Email Data

Authors:
Anurat Chapanond;Mukkai S. Krishnamoorthy;Bülent Yener
Affiliations:
Department of Computer Science Rensselaer Polytechnic Institute, Troy 12180;Department of Computer Science Rensselaer Polytechnic Institute, Troy 12180;Department of Computer Science Rensselaer Polytechnic Institute, Troy 12180
Venue:
Computational & Mathematical Organization Theory
Year:
2005

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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.