Research on Overlapping Node Mining Model for Important Information Dissemination in Social Networks
This paper addresses the problem of community detection in dynamic social networks and propo-ses a Social Network Overlapping Node Mining Model(SNONMM),and aims at the efficient detection of overlapping communities in dynamic social networks.The model combines the Label Propagation Algo-rithm(LPA)and the Spreading Activation principle to achieve efficient detection of overlapping communi-ties in dynamic social networks.In this approach,new nodes have a greater chance of spreading their la-bels to other nodes in the social network than that of old nodes,making new nodes more easily discovered and incorporated into their respective communities.At the same time,activation values are introduced to represent the propagation strength of each label,which helps to more accurately capture changes in com-munity structure.To validate the effectiveness of the proposed method,its performance was evaluated u-sing two real-world datasets and a synthetic network.Experimental results demonstrate that the proposed method outperforms other available methods in terms of community detection accuracy.
dynamic social networkscommunity detectionlabel propagation algorithmdiffusion activa-tion
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