Analysis Of Message Credibility Detections In Complex Networks

The Internet plus era has already arrived at side us unconsciously. Recent years, the Internet industry has a fast development. Especially the speed of the growth of the moving Web is shocking, more and more people can log on the Internet more conveniently than before. And the way of the message spread transfers from the traditional word of mouth only in the life circle of acquaintances to the Internet, the message spread becomes faster and faster, and affects more and more widely. The network has become an important medium for news spreading.The message spread on complex networks in these last several days has been a concern of experts and scholars. The propagation process of message and infectious virus is similar, the study of the propagation the messages has been on account of the infectious disease models. In the human relations network, everybody is a node, and the relationship between people is an edge of complex network. The Topology Configuration of Social Network topology is not a stochastic shape or a random graph, but close to the complex network which possess small-world qualities and no-scale characteristics. This network is characterized by a huge number of nodes, and complex relationships between nodes, each individual’s behavior is different, which has different effects.In order to study the propagation process of the message which has different credibility on the complex network, my article has come up a new message propagation model(SIDO) based on epidemic model. This model integrated the traditional epidemic SIR model and SIS model, adding 2 new node status, S refers to the node in an unknown state, I stands for node is in spread state, D stands for the doubtful condition and it chooses not to propagation the news, O stands for opponents of the message.In recent decades, depending on the development of the computer, the study of s theory, modeling and empirical analysis in complex networks has been made impressive achievements. Depends on the development of computer technology, especially the development of computer simulation technology, we made a lot of achievements in complex networks. We have learned that there are many large and complex networks in the real world, such as personal relationship networks, the actor cooperation network, weibo attention relationships system, traffic systems web, large-scale power networks, cellular networks, metabolic networks, and so on.Research on complex networks can help us apprehend, regulate and direct the public opinion spread on complex networks better. And in order to make a breakthrough in theory, we need to support the experiment research, it is necessary to promote the development of complex network theory in empirical research with a view to settle real-world matters better. Especially since the 90 s of last century, humans have a life filled with a variety of complex networks, we need to solve many problems from the perspective of complex networks. The research of complex networks have deepen people’s learning about the evolving world. Study of complex networks provides us a fresh angle and a new approach for the settle of many true life complex networks. The scholar literature of complex networks has historic and momentous effect in both theory and actually real-world using.