NDLI: Social network analysis for email classification

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Social network analysis for email classification

Content Provider	ACM Digital Library
Author	Yelupula, K. Ramaswamy, Srini
Abstract	The availability of a large corpus of emails in organizations, such as the Enron dataset (used in this work), is the motivation for this work. The attempt is to see if one can predict the organizational structure of Enron by using data mining algorithms and methodologies on this email dataset. The primary approach in this attempt is the analysis of email flows within the organization. Our results show that significant information about an organization's structure can be obtained even if the body (content) of emails is neglected. Enough relevant data is extracted about the 'email' social network using simple email flow analysis and associated statistics gaining an over all picture of the organizational structure. The longer term objective of this work is to show that readily available information can be used to determine relevant metrics by which one can reconstruct and verify the approximate social hierarchies within an organization or company.
Starting Page	469
Ending Page	474
Page Count	6
File Format	PDF
ISBN	9781605581057
DOI	10.1145/1593105.1593229
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2008-03-28
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Mining e-mail archives Data mining Business organization structures
Content Type	Text
Resource Type	Article

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