Abstract
For the analysis of communities in social networks several data mining techniques have been developed such as the DenGraph algorithm to study the dynamics of groups in graph structures. The here proposed DenGraph-HO algorithm is an extension of the density-based graph clusterer DenGraph. It produces a cluster hierarchy that can be used to implement a zooming operation for visual social network analysis. The clusterings in the hierarchy fulfill the DenGraph-O paradigms and can be efficiently computed. We apply DenGraph-HO on a data set obtained from the music platform Last.fm and demonstrate its usability.
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Acknowledgements
This work was supported by the members of the distributedDataMining BOINC [1] project (http://www.distributedDataMining.org).
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Schlitter, N., Falkowski, T., L¨assig, J. (2011). DenGraph-HO: Density-based Hierarchical Community Detection for Explorative Visual Network Analysis. In: Bramer, M., Petridis, M., Nolle, L. (eds) Research and Development in Intelligent Systems XXVIII. SGAI 2011. Springer, London. https://doi.org/10.1007/978-1-4471-2318-7_22
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DOI: https://doi.org/10.1007/978-1-4471-2318-7_22
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