Communication structure discovery via information asymmetry in an organizational social network

Cheng-Te Li, Shou De Lin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In an organization, based on the positions of employees there is usually an existing hierarchy among them. However, in real-life cases, people's interactions tend to form a certain communication structure due to some external forces or personal factors. In this paper, we aim at discovering the potential communication structure, in which nodes are typed labels (e.g. job-titles) and edges stand for tight interactions between typed labels in an organizational social network. To tackle this problem, we propose to exploit the concept of information asymmetry to model the core-periphery property in the communication structure. The proximity asymmetry is defined to realize the information asymmetry. We also devise two random-walk methods to calculate the proximity asymmetry between typed labels. The experiments conducted on the Enron email dataset shows that the proposed method outperforms some heuristic ones.

Original languageEnglish
Title of host publication2010 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2010
Pages524-527
Number of pages4
DOIs
Publication statusPublished - 2010 Dec 13
Event2010 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2010 - Toronto, ON, Canada
Duration: 2010 Aug 312010 Sep 3

Publication series

NameProceedings - 2010 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2010
Volume1

Other

Other2010 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2010
CountryCanada
CityToronto, ON
Period10-08-3110-09-03

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Software

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