关键词: 复杂网络, k-shell, 加权度, 影响力识别

Abstract: Nodes that have greater influence in complex networks play an important role in controlling rumors propagation, optimizing resource allocation, spreading information efficiently, and advertising accurately. In view of the current many methods in identifying the node’s influence have certain limitation, this paper based on the k-shell algorithm defines the concept of weighted degree, and puts forward the Modified k-shell（MKS） algorithm, shorted for MKS algorithm by measuring the potential importance of edges and considering the different contributions of neighbors. This algorithm considers the nodes’own features, location features and local features. Through implementing this algorithm on the representative Zachary karate club network and comparing with other typical methods, it is found that this algorithm improves the coarse division of k-shell algorithm, and its result is more reasonable.

Key words: complex networks, k-shell, weighted degree, influence identification