Experimental Researches Of Calculating Characteristics And Identifying Key-node In Social Network

With the development of web2.0, social networking has also developed quickly, the emergence of various types of social networking sites and services, not only greatly enriching people’s lives, but also on human social behavior and lifestyle have had a profound change. Research on social networks related fields is a hot of current network research. Because of the unique status and role of social networks, it has a profound impact on every aspect of people’s social life, but also related to public opinion, social security and even national security, therefore, the study of social networks is of great significance.In this paper, social networks, based on complex network theory and improved ADWP (Activity degree weighted Pagerank) algorithm, using graph theory and complex network modeling tools Networkx. to identify the characteristics and key node in the social network analysis and research carried out experiments. The main work of this paper includes:1Based on the theory of complex networks, social network for the topology to Tencent microblogging represented, calculating the relevant scale and small-world characteristics, in Networkx platform, validating these two features, and having done experimental analysis.2thoughts on topology changes, and contraction method using the delete method to evaluate the importance of nodes, proposed an improved ADWP key node recognition algorithm. Firstly, a detailed description and analysis of the key node identification algorithm based on PageRank. and then, on this basis, the introduction of this important factor of social network users "activity" in the weight distribution is improved. That is the basis for allocation of link-based PageRank is based on the increase in the user’s "activity" as the weight distribution index, the better characterize the social networking features, improve and refine the original PageRank algorithm to identify the key nodes. Finally, under Networkx environment to Tencent microblogging forwarding network, for example, to verify the effectiveness of the basic ideas and identify key nodes algorithm.In summary, this paper based on Networkx environment characterized by social networks from complex network computing and identifying critical nodes found in both experimental analysis and research. Research work in this paper has some cutting-edge,for the same work, but also has some theoretical reference value.