Research of Wechat Network Information Transmission based on the Complex Network

Abstract

In the recent three years, Wechat quickly developed into the most popular social networking platform. The topology structure of Wechat is analyzed through description of the basic data of the Wechat network and complex network analysis method. When building social networks Tencent Wechat, we get statistical properties such as the degree distribution, aggregation coefficient, and average path length complex networks. The scale-free characteristic of the Wechat network and small world properties are figured out. Research of complex network System is an organic whole made up of the parts of interdependence and interaction with specific functions. Network is constituted by nodes and the attachment, if express elements of the system in node, and use the connection between the two nodes to say the interaction between system elements, then the network provide a new way to study system. As a highly abstract of large number real complex systems, complex networks become a new research hotspot in the international academia in recent years; domestic scholars have started this research. Development evolution process of classical complex network model One of the simplest cases of network is regular net. It refers to the relationship between each element in the system can use some regular structure to represent, namely link between any two nodes in the network follow the established rules. But because of the complexity of the network itself, large scale network can not completely use rule to represent. In the late 1950s, Erdos and Renyi proposed a completely random network model, stochastic network, it is the network formed by randomly link in probability P of any two nodes in the graph, namely whether the two nodes connected is no longer a sure thing, but decided by the probability P. [1]Random networks and regular rules are two extreme situations. With the continuous development of technology, the scientists found that for a large number of real network systems, they are neither a network of rules nor random, but somewhere in between. 1) Small world network In 1998, Watts and Strogatz proposed WS network model (small world network); its construction algorithm are as follows: (1) From the beginning of the regular graph, considering a nearest neighbor coupled network containing N points, they round into a ring, in which each node is connected with nodes it around each K / 2, K is even. (2) Randomization reconnection: reconnect the network of each edge in probability P randomly; namely the edge of an endpoint remains unchanged, while the other one endpoint taken as randomly a node in a network. Which regulates, between any two different stages up to only by an edge, and each node can have side connected to itself. 2) Scale-free networks In order to explain the mechanism of power-law distribution, BA network model is put forward by Barabasi and Albert in 1999, introducing two neglected important features in the network structure in the small world network: (1) Growth: it refers to that constantly have new node in the network to join in. [2] For example, every day there a large number of new pages on the WWW are born.