A genetic algorithm approach for detecting hierarchical and overlapping community structure in dynamic social networks

Chun Cheng Lin, Wan Yu Liu, Der-Jiunn Deng

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

6 Citations (Scopus)

Abstract

Social networks are merely a reflection of certain realities among people that have been identified. But in order for people or even computer systems (such as expert systems) to make sense of the social network, it needs to be analyzed with various methods so that the characteristics of the social network can be understood in a meaningful context. This is challenging not only due to the number of people that can be on social networks, but the changes in relationships between people on the social network over time. In this paper, we develop a method to help make sense of dynamic social networks. This is achieved by establishing a hierarchical community structure where each level represents a community partition at a specific granularity level. By organizing each level of the hierarchical community structure by granularity level, a person can essentially 'zoom in' to view more detailed (smaller) communities and 'zoom out' to view less detailed (larger) communities. Communities consisting of one or more subsets of people having relatively extensive links with other communities are identified and represented as overlapping community structures. Mechanisms are also in place to enable modifications to the social network to be dynamically updated on the hierarchical and overlapping community structure without recreating it in real time for every modification. The experimental results show that the genetic algorithm approach can effectively detect hierarchical and overlapping community structures.

Original languageEnglish
Title of host publication2013 IEEE Wireless Communications and Networking Conference, WCNC 2013
Pages4469-4474
Number of pages6
DOIs
Publication statusPublished - 2013 Aug 21
Event2013 IEEE Wireless Communications and Networking Conference, WCNC 2013 - Shanghai, China
Duration: 2013 Apr 72013 Apr 10

Other

Other2013 IEEE Wireless Communications and Networking Conference, WCNC 2013
CountryChina
CityShanghai
Period13-04-0713-04-10

Fingerprint

Expert systems
Computer systems
Genetic algorithms

All Science Journal Classification (ASJC) codes

  • Engineering(all)

Cite this

Lin, C. C., Liu, W. Y., & Deng, D-J. (2013). A genetic algorithm approach for detecting hierarchical and overlapping community structure in dynamic social networks. In 2013 IEEE Wireless Communications and Networking Conference, WCNC 2013 (pp. 4469-4474). [6555298] https://doi.org/10.1109/WCNC.2013.6555298
Lin, Chun Cheng ; Liu, Wan Yu ; Deng, Der-Jiunn. / A genetic algorithm approach for detecting hierarchical and overlapping community structure in dynamic social networks. 2013 IEEE Wireless Communications and Networking Conference, WCNC 2013. 2013. pp. 4469-4474
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Lin, CC, Liu, WY & Deng, D-J 2013, A genetic algorithm approach for detecting hierarchical and overlapping community structure in dynamic social networks. in 2013 IEEE Wireless Communications and Networking Conference, WCNC 2013., 6555298, pp. 4469-4474, 2013 IEEE Wireless Communications and Networking Conference, WCNC 2013, Shanghai, China, 13-04-07. https://doi.org/10.1109/WCNC.2013.6555298

A genetic algorithm approach for detecting hierarchical and overlapping community structure in dynamic social networks. / Lin, Chun Cheng; Liu, Wan Yu; Deng, Der-Jiunn.

2013 IEEE Wireless Communications and Networking Conference, WCNC 2013. 2013. p. 4469-4474 6555298.

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

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Lin CC, Liu WY, Deng D-J. A genetic algorithm approach for detecting hierarchical and overlapping community structure in dynamic social networks. In 2013 IEEE Wireless Communications and Networking Conference, WCNC 2013. 2013. p. 4469-4474. 6555298 https://doi.org/10.1109/WCNC.2013.6555298