Comparative definition of community and corresponding identifying algorithm
Comparative definition of community and corresponding identifying algorithm
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社区的比较定义及相应的识别算法
DOI：
10.1103/physreve.78.026121
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发表时间：
2008-08-01
影响因子：
2.4
通讯作者：
Fan, Ying
中科院分区：
文献类型：
--
作者：
Hu, Yanqing;Chen, Hongbin;Fan, Ying
提出了网络社区的比较定义，并给出了相应的检测算法。社区被定义为节点的集合，满足社区内每个节点的度数不小于该节点对其他社区的度数的要求。在算法中，社区对节点的吸引力定义为社区之间的联系。然后采用基于吸引力的自组织过程，无需任何额外参数，就可以检测到最佳社区。分析了几个人工和现实世界的网络，包括 Zachary 空手道俱乐部、大学橄榄球和大型科学合作网络。该算法在检测社区方面效果很好，并且还很好地描述了网络划分和群体形成。
A comparative definition for community in networks is proposed, and the corresponding detecting algorithm is given. A community is defined as a set of nodes, which satisfies the requirement that each node's degree inside the community should not be smaller than the node's degree toward any other community. In the algorithm, the attractive force of a community to a node is defined as the connections between them. Then employing an attractive-force-based self-organizing process, without any extra parameter, the best communities can be detected. Several artificial and real-world networks, including the Zachary karate club, college football, and large scientific collaboration networks, are analyzed. The algorithm works well in detecting communities, and it also gives a nice description of network division and group formation.