Content-centric flow mining for influence analysis in social streams

Karthik Subbian, Charu Aggarwal, Jaideep Srivastava

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

17 Citations (Scopus)

Abstract

The problem of discovering information flow trends and influencers in social networks has become increasingly relevant both because of the increasing amount of content available from online networks in the form of social streams, and because of its relevance as a tool for content trends analysis. An important part of this analysis is to determine the key patterns of flow and corresponding influ-encers in the underlying network. Almost all the work on influence analysis has focused on fixed models of the network structure, and edge-based transmission between nodes. In this paper, we propose a fully content-centered model of flow analysis in social network streams, in which the analysis is based on actual content transmissions in the network, rather than a static model of transmission on the edges. First, we introduce the problem of information flow mining in social streams, and then propose a novel algorithm In-FlowMine to discover the information flow patterns in the network. We then leverage this approach to determine the key influencers in the network. Our approach is flexible, since it can also determine topic-specific influencers. We experimentally show the effectiveness and efficiency of our model.

Original languageEnglish
Title of host publicationInternational Conference on Information and Knowledge Management, Proceedings
Pages841-846
Number of pages6
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event22nd ACM International Conference on Information and Knowledge Management, CIKM 2013 - San Francisco, CA
Duration: 27 Oct 20131 Nov 2013

Other

Other22nd ACM International Conference on Information and Knowledge Management, CIKM 2013
CitySan Francisco, CA
Period27/10/131/11/13

Fingerprint

Information flow
Social networks
Trend analysis
Node
Leverage
Network structure

Keywords

  • Content analysis
  • Flow mining
  • Influence analysis

ASJC Scopus subject areas

  • Business, Management and Accounting(all)
  • Decision Sciences(all)

Cite this

Subbian, K., Aggarwal, C., & Srivastava, J. (2013). Content-centric flow mining for influence analysis in social streams. In International Conference on Information and Knowledge Management, Proceedings (pp. 841-846) https://doi.org/10.1145/2505515.2505626

Content-centric flow mining for influence analysis in social streams. / Subbian, Karthik; Aggarwal, Charu; Srivastava, Jaideep.

International Conference on Information and Knowledge Management, Proceedings. 2013. p. 841-846.

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

Subbian, K, Aggarwal, C & Srivastava, J 2013, Content-centric flow mining for influence analysis in social streams. in International Conference on Information and Knowledge Management, Proceedings. pp. 841-846, 22nd ACM International Conference on Information and Knowledge Management, CIKM 2013, San Francisco, CA, 27/10/13. https://doi.org/10.1145/2505515.2505626
Subbian K, Aggarwal C, Srivastava J. Content-centric flow mining for influence analysis in social streams. In International Conference on Information and Knowledge Management, Proceedings. 2013. p. 841-846 https://doi.org/10.1145/2505515.2505626
Subbian, Karthik ; Aggarwal, Charu ; Srivastava, Jaideep. / Content-centric flow mining for influence analysis in social streams. International Conference on Information and Knowledge Management, Proceedings. 2013. pp. 841-846
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