Research on Community Characteristics of Multi-source Social Network

In order to analyze the impact of social networks on the spread of public opinion, the multi-source network community structure characteristics and its propagation characteristics was studied. Furthermore, the overlapping community was discussed using COPRA algorithm and LFM algorithm in social network and the improved algorithm of LFM based on filtering node degree, named as NF-LFM algorithm, was proposed. In this algorithm, the node with node degree less than a certain threshold in the friend relation network was filtered, and then the rest of the network was divided into community structure. The results showed that the social networks such as Renren, Qzone and Microblog had obvious characteristics of the community structure, of which Renren and Qzone was stronger than Microblog. Without taking into account the user activity, the diffusion range of public opinion information in Renren was larger than the others. The proposed method could not only solve the resolution problem of the existing algorithm in the community division results effectively, but also make up for the shortcomings of the LFM algorithm, which was caught in an infinite iterative process and leads to high time complexity. It was also in line with expected results when it was applied to the classical data set. The results can help researchers understand the impact on public opinion spread in community. It also has important significance for the discovery of network group incidents and guidance of public sentiment. © 2017, Editorial Department of Advanced Engineering Sciences. All right reserved.