Paper Info
Title
Social network analysis for email classification
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.
Year
DOI
Venue
2008
10.1145/1593105.1593229
ACM Southeast Regional Conference 2005
Keywords
Field
DocType
relevant data,email dataset,approximate social hierarchy,enron dataset,email classification,relevant metrics,available information,organizational structure,email flow,data mining algorithm,social network analysis,simple email flow analysis,data mining,flow analysis,structured data,social network
Data science,Data mining,Organizational network analysis,Social network,Organizational structure,Computer science,Social stratification,Social network analysis,Email classification,Data mining algorithm
Conference
Citations 
PageRank 
References 
11
0.62
2
Authors
2
Name
Order
Citations
PageRank
K. Yelupula1110.62
srini ramaswamy233745.77