An Extension to Hub Algorithm Based on Triangular Loop

The algorithm of breadth first traversal in graph has been widely applied in community detection. Some community detection algorithms based on the breadth first traversal usually use the largest node the largest as the initial node. And these algorithms determine a node belongs to which community according to the number of the edges from the node to the communities. And then in the high aggregated networks, the results of community detection are not appropriate. The algorithm in this paper extends the Hub algorithm. This algorithm puts forward the concept of the degree of triangular loop of nodes, and use it to find the center of community. In the process of community detecting, this algorithm defines the concept of the similarity coefficient. And based on the similarity coefficient, this algorithm determines which community the nodes belong to, as well as adjusts the results of community detecting. The experiment confirms that the algorithm in this paper can not only guarantee the feasibility but also improve the quality of community detecting.