Abstract
Based on the new concept of central network and the node similarity definition, a fast algorithm is proposed for discovering community structures in social networks. Firstly, start from the maximum degree node, then the two nodes with the maximum number of shared neighbors are taken as the initial community. Next, a neighboring node is judged to push into the initial community according to the appearance frequency of the community it belongs to. Finally, the above step is repeated until all the nodes are classified to the proper communities. The experimental results on two real-world networks demonstrate that the proposed algorithm is able to discover community structure from a given network efficiently and accurately without specifying the community number. The algorithm has a time complexity of only O(n).
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Fang, P., Shi, F., Chen, Y., Gao, W. (2013). Community Discovering Based on Central Nodes of Social Networks. In: Sun, Z., Deng, Z. (eds) Proceedings of 2013 Chinese Intelligent Automation Conference. Lecture Notes in Electrical Engineering, vol 256. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38466-0_33
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DOI: https://doi.org/10.1007/978-3-642-38466-0_33
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