Graph Theoretic and Spectral Analysis of Enron Email Data View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2005-10

AUTHORS

Anurat Chapanond, Mukkai S. Krishnamoorthy, Bülent Yener

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. More... »

PAGES

265-281

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10588-005-5381-4

DOI

http://dx.doi.org/10.1007/s10588-005-5381-4

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1027382549


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