The Social Network Topology Model Based On The Transmission Of Information And Behavior

The relationship between things in nature and human society always can be described inthe graph. The iconicity and direct viewing of the graphical description can make peopleeasily understand and accept. Just for this reason, almost all of the research on networktopology structure used a lot of knowledge of graph theory. The topology modeling study is toexplore unknown rules of large complex networks. Initially, researchers simply viewed therelationship between individuals in the network as the link between nodes in the graph. Withthe deepening of the study on network topology, researchers found that simply treating anindividual as a node and relationship between individuals as an edge only roughly reflectedthe real topology of network from macroscopic viewpoint, but it could not reflect the specificrelationship between individuals in the network. Therefore, on the basis of the existing study,researchers assigned a weight for every edge between the nodes and generated a weightedundirected graph, where the weight represented the specific relationship between individuals.On the basis of the weighted undirected graph, some researchers constructed a weighteddirected topology model, such as BBV model.Although based on the weighted undirected network topology model can reflect the realnetwork topology structure from macroscopic viewpoint and also can reflect the specificrelationship between individuals in the network to a certain extent, but considering thatconnections between individuals in real network are generally directed and connectionsbetween different individuals are generally different. If not considering these two practicalsituation, it obviously could not reflect the real relationship between individuals in realnetwork, so some researchers began to simulate network topology structure using theweighted directed graph and constructed network topology model based on the weighteddirected graph.In this paper, considering the phenomenon of recommendation existed in real network, Iproposed a weighted directed network topology model, and introduced the triad formationrule as the evolution rules of the network with the preferential rule. Moreover, I analyzed themodel through the simulation experiment on the degree distribution and clusteringcharacteristics.In recent years, the social network based on the real interpersonal relationship networkgrows fast, and gradually blends into our daily life, even plays an important role. Through thestudy of topology structure of the social network, we can understand features and behaviors ofusers, and analyze the content, features, mode and impact of information transmission and behavior dissemination. The study of topology structure of the social network has importanttheoretical value and practical significance.Based on the complex network topology theory, this paper analyzed the disseminationcharacteristics of information and behavior, and proposed a social network topology model.This model focused on the following two aspects:(1)This model took the weighted and directed characteristics of the real social networkinto consideration. Namely, the dissemination of information and behavior in a social networkalways has a certain point, and the dissemination ability of each node is different. Thefrequency or strength of different nodes in the transmission of information and behavior isalso different, so in the process of constructing the model, this paper not only distinguishedthe directions of the links between different nodes, but also the efficiency of dissemination indifferent directions. In our model, each directed edge was assigned a weight, which waschanged along with the time and spatial evolution of the model.(2)In order to well simulate the real social network, the model introduced the triadformation rule as the evolution rule based on the clustering structure of the real social network.Because of the introduction of the triad formation, the model can generate topology structurewith high clustering characteristics.Simulation results showed the degree and strength distribution as well as the correlationbetween degree and strength of the network generated by the topology model embodiedobvious power-law characteristic, and meanwhile, through analyzing the clustering coefficient,coreness and Gini coefficient of the network, we verified that the generated network had thecharacteristics of clustering, layer and heterogeneity which were shown in the real friendshipnetwork.