Graph Theoretic and Spectral Analysis of Enron Email Data Export

@article{citeulike:2611257, abstract = {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.}, author = {Chapanond, Anurat and Krishnamoorthy, Mukkai and Yener, B\"{u}lent}, citeulike-article-id = {2611257}, citeulike-linkout-0 = {http://dx.doi.org/10.1007/s10588-005-5381-4}, day = {14}, doi = {10.1007/s10588-005-5381-4}, journal = {Computational \& Mathematical Organization Theory}, keywords = {corpus\_analysis, email, project--email, social\_network\_analysis}, month = {October}, number = {3}, pages = {265--281}, posted-at = {2008-03-29 23:16:40}, priority = {2}, title = {Graph Theoretic and Spectral Analysis of Enron Email Data}, url = {http://dx.doi.org/10.1007/s10588-005-5381-4}, volume = {11}, year = {2005} }

TY - JOUR ID - citeulike:2611257 L3 - citeulike-article-id:2611257 N2 - 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. IS - 3 JF - Computational & Mathematical Organization Theory EP - 281 TI - Graph Theoretic and Spectral Analysis of Enron Email Data VL - 11 SP - 265 KW - corpus_analysis KW - email KW - project--email KW - social_network_analysis AU - Chapanond, Anurat AU - Krishnamoorthy, Mukkai AU - Yener, Bülent PY - 2005/10/14/ UR - http://dx.doi.org/10.1007/s10588-005-5381-4 ER -