The Research Of Rumor Dissemination On Social Network

Social network refers to a structure established on people’s relationship. From the perspective of sociology, it is a product of the interplay between people’s relations. With the increasingly development of the Internet, social network has become familiar to all people. When it comes to social network, it is believed that people naturally think of the widely application of Facebook, Twittter to the net. In the recent years, communication network has become increasingly widespread. Social network service has become the most widely override and it has the greatest commercial value. The information in the social network nearly spread all the time, such as that in these fields: fashion, news, views, rumors, and the like. In the above information, some have a positive impact on the society while others have a negative impact on the society. And one of the most striking is the rumor. In the human’s life with a long history, rumor has not always been considered as a decent word. And in the process of using social network applications, we found that the influence of Internet rumor is greater than traditional rumor. Once rumor spread on social network, it is difficult to control, and it can bring serious impact to social media.In this paper, the main work is to research the inner-model of social network and analyze its characteristics. Furthermore, I combine this model with the concept of rumor spreading to find a more effective method to control the spread of rumor. First, I introduce the basic concept of social network and rumor, their current status of development and research results. Second, I propose a rumor spreading mechanism based on SCIR model. Through the analysis of the mathematical, I get some important conclusions, and the numerical simulation verifies the correctness of the theoretical analysis. Third, we are inspired by the thought of worm propagation in computer network. We add a mechanism of anti-rumor into our rumor spreading model. Through numerical simulation experiment, I come to the conclusion that the mechanism has a certain impact on rumor spreading. Finally, in order to better control the spread of the rumor in social network, I proposed a clustering algorithm based on weights and attributes. Through this method, we classify all the nodes in the network. Classify those nodes who make great contributions to the rumor spreading into a cluster. Then those nodes can help to control the spread of rumor better.