Research On Maximization Of Social Network Influence And Its Application In Network Marketing

In recent years, the rapid development of large social networks provides great convenience to people. Meanwhile, social networks are influencing people’s behaviour patterns of self-expressing, interaction and entertainment. Establishing a rational evaluation system of nodes’ influence in social networks is of great significance for the research of influence distribution and propagation mode between the nodes of the network. The evaluation of nodes’s influence is not only an important information source for the decision of network public opinion guiders, but also a vital basis for the selection of seed nodes in viral marketing.This thesis presents a multiple attribute decision making method-TOPSIS method as the main research method. An extension approach of TOPSIS method based in the entropy-weight method is proposed to apply in network nodes’ influence evaluation model. The main contents are as follows.Firstly, the thesis introduces the basic concepts of the entropy weight method, TOPSIS method and background of social network influence and network marketing. Next, common methods of evaluation of network nodes’ influence is introduced, including identifying methods of influencial nodes and the problem about maximization of influence in networks. Then the thesis focuses on the research of TOPSIS method. The thesis defines the weight of multiple attributes in TOPSIS method with the concept of entropy and proposes an extension of TOPSIS method based in the entropy weight method., which will improve the objectivity of the weights of the attributes in the TOPSIS method. Furthermore, by comparing the reference of historical literature, the thesis select the typical social network analysis centrality index. Finally, the new improved TOPSIS method is applied to analysis network marketing in node’s influence evaluation. And SI model will be used to prove the effectiveness and superiority of the new method.