Research on Fast Community Detection Algorithm in Microblog

Article Preview

Abstract:

According to the problem of extracting the community structure of large networks, we propose a simple heuristic method based on community coding optimization. It is shown to outperform the InfoMap community detection method in terms of computation time. Experiments show that our method can find out various communities in microblog, which reveal the core structure of the network.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

2045-2049

Citation:

Online since:

February 2014

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] S.E. Schaeffer. Graph clustering. Computer Science Review, 1(1): 27–64, (2007).

Google Scholar

[2] U. Brandes, M. Gaertler, and D. Wagner. Engineering graph clustering: Models and experimental evaluation. Journal of Experimental Algorithmics, 12(1), (2007).

Google Scholar

[3] U. von Luxburg. A tutorial on spectral clustering. Technical Report 149, Max Plank Institute for Biological Cybernetics, August (2006).

Google Scholar

[4] S.E. Schaeffer. Graph clustering. Computer Science Review, 1(1): 27–64, (2007).

Google Scholar

[5] M.E.J. Newman. Modularity and community structure in networks. Proceedings of the National Academy of Sciences of the United States of America, 103(23): 8577–8582, (2006).

DOI: 10.1073/pnas.0601602103

Google Scholar

[6] M.E.J. Newman and M. Girvan. Finding and evaluating community structure in networks. Physical Review E, 69: 026113, (2004).

Google Scholar

[7] Martin Rosvall, Carl T. Bergstrom. Maps of random walks on complex networks reveal community structure, Proceedings of the National Academy of Sciences of the United States of America, 2008 105(4) 1118-1123.

DOI: 10.1073/pnas.0706851105

Google Scholar

[8] Vincent D Blondel, Jean-Loup Guillaume, Renaud Lambiotte, ET al. Fast unfolding of communities in large networks. ArXiv ePrint: 0803. 0476, (2008).

Google Scholar