Analyzing the propagation of influence and concept evolution in enterprise social networks through centrality and latent semantic analysis

Weizhong Zhu, Chaomei Chen, Robert B. Allen

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

3 Citations (Scopus)

Abstract

Understanding the propagation of influence and the concept flow over a network in general has profound theoretical and practical implications. In this paper, we propose a novel approach to ranking individual members of a real-world communication network in terms of their roles in such propagation processes. We first improve the accuracy of the centrality measures by incorporating temporal attributes. Then, we integrate weighted PageRank and centrality scores to further improve the quality of these measures. We valid these ranking measures through a study of an email archive of a W3C working group against an independent list of experts. The results show that time-sensitive Degree, time-sensitive Betweenness and the integration of the weighted PageRank and these centrality measures yield the best ranking results. Our approach partially solves the rank sink problem of PageRank by adjusting flexible jumping probabilities with Betweenness centrality scores. Finally the text analysis based on Latent Semantic Indexing extracts key concepts distributed in different time frames and explores the evolution of the discussion topics in the social network. The overall study depicts an overview of the roles of the actors and conceptual evolution in the social network. These findings are important to understand the dynamics of the social networks.

Original languageEnglish
Title of host publicationAdvances in Knowledge Discovery and Data Mining - 12th Pacific-Asia Conference, PAKDD 2008, Proceedings
Pages1090-1098
Number of pages9
DOIs
Publication statusPublished - 2008 Jun 10
Event12th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2008 - Osaka, Japan
Duration: 2008 May 202008 May 23

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5012 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other12th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2008
CountryJapan
CityOsaka
Period08/5/2008/5/23

Fingerprint

Latent Semantic Analysis
Centrality
Electronic mail
Social Networks
PageRank
Telecommunication networks
Semantics
Propagation
Ranking
Betweenness
Industry
Latent Semantic Indexing
Text Analysis
Electronic Mail
Communication Networks
Attribute
Integrate
Valid
Concepts
Influence

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Zhu, W., Chen, C., & Allen, R. B. (2008). Analyzing the propagation of influence and concept evolution in enterprise social networks through centrality and latent semantic analysis. In Advances in Knowledge Discovery and Data Mining - 12th Pacific-Asia Conference, PAKDD 2008, Proceedings (pp. 1090-1098). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5012 LNAI). https://doi.org/10.1007/978-3-540-68125-0_118
Zhu, Weizhong ; Chen, Chaomei ; Allen, Robert B. / Analyzing the propagation of influence and concept evolution in enterprise social networks through centrality and latent semantic analysis. Advances in Knowledge Discovery and Data Mining - 12th Pacific-Asia Conference, PAKDD 2008, Proceedings. 2008. pp. 1090-1098 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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Zhu, W, Chen, C & Allen, RB 2008, Analyzing the propagation of influence and concept evolution in enterprise social networks through centrality and latent semantic analysis. in Advances in Knowledge Discovery and Data Mining - 12th Pacific-Asia Conference, PAKDD 2008, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5012 LNAI, pp. 1090-1098, 12th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2008, Osaka, Japan, 08/5/20. https://doi.org/10.1007/978-3-540-68125-0_118

Analyzing the propagation of influence and concept evolution in enterprise social networks through centrality and latent semantic analysis. / Zhu, Weizhong; Chen, Chaomei; Allen, Robert B.

Advances in Knowledge Discovery and Data Mining - 12th Pacific-Asia Conference, PAKDD 2008, Proceedings. 2008. p. 1090-1098 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5012 LNAI).

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

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AB - Understanding the propagation of influence and the concept flow over a network in general has profound theoretical and practical implications. In this paper, we propose a novel approach to ranking individual members of a real-world communication network in terms of their roles in such propagation processes. We first improve the accuracy of the centrality measures by incorporating temporal attributes. Then, we integrate weighted PageRank and centrality scores to further improve the quality of these measures. We valid these ranking measures through a study of an email archive of a W3C working group against an independent list of experts. The results show that time-sensitive Degree, time-sensitive Betweenness and the integration of the weighted PageRank and these centrality measures yield the best ranking results. Our approach partially solves the rank sink problem of PageRank by adjusting flexible jumping probabilities with Betweenness centrality scores. Finally the text analysis based on Latent Semantic Indexing extracts key concepts distributed in different time frames and explores the evolution of the discussion topics in the social network. The overall study depicts an overview of the roles of the actors and conceptual evolution in the social network. These findings are important to understand the dynamics of the social networks.

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Zhu W, Chen C, Allen RB. Analyzing the propagation of influence and concept evolution in enterprise social networks through centrality and latent semantic analysis. In Advances in Knowledge Discovery and Data Mining - 12th Pacific-Asia Conference, PAKDD 2008, Proceedings. 2008. p. 1090-1098. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-540-68125-0_118