Automated social hierarchy detection through email network analysis

Ryan Rowe, German Creamer, Shlomo Hershkop, Salvatore J. Stolfo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

95 Scopus citations

Abstract

This paper provides a novel algorithm for automatically extracting social hierarchy data from electronic communication behavior. The algorithm is based on data mining user behaviors to automatically analyze and catalog patterns of communications between entities in a email collection to extract social standing. The advantage to such automatic methods is that they extract relevancy between hierarchy levels and are dynamic over time. We illustrate the algorithms over real world data using the Enron corporation's email archive. The results show great promise when compared to the corporations work chart and judicial proceeding analyzing the major players.

Original languageEnglish
Title of host publicationJoint Ninth WebKDD and First SNA-KDD Worshop 2007 on Web Mining and Social Network Analysis
Pages109-117
Number of pages9
DOIs
StatePublished - 2007
EventJoint 9th WebKDD and 1st SNA-KDD Workshop 2007 on Web Mining and Social Network Analysis. Held in conjunction with 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2007 - San Jose, CA, United States
Duration: 12 Aug 200715 Aug 2007

Publication series

NameJoint Ninth WebKDD and First SNA-KDD 2007 Workshop on Web Mining and Social Network Analysis

Conference

ConferenceJoint 9th WebKDD and 1st SNA-KDD Workshop 2007 on Web Mining and Social Network Analysis. Held in conjunction with 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2007
Country/TerritoryUnited States
CitySan Jose, CA
Period12/08/0715/08/07

Keywords

  • Behavior profile
  • Data
  • Enron
  • Link mining
  • Mining
  • Social network

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