Research On Topological Evolution And Information Interaction Of Social Networks From The Perspective Of Bidirectional Preferential Attachment

The topological evolution and information interaction on social networks have been widely studied in many fields,such as information science,natural science,social science and management science,which have typical interdisciplinary characteristics and become an important research hotspot.The information interaction and dissemination on social networks depend on the topological structure of social networks,so the law of information dissemination is closely related to the topological structure of social networks.The information flow between people is the direct driving force of the topological structure evolution and information dissemination of social networks,but the researches on the topological structure evolution mechanism and information dissemination rules of social networks from the characteristics of information interaction between individuals are few.Based on the big data of social network information dissemination,this paper studies the relationship and logic among network topology,individual behavior characteristics and information interaction from the perspective of bidirectional priority preferential mechanism,and finds the mechanism and law of information dissemination in social network,and proposes the information interaction model and information dissemination model which is different from the traditional SIR model.At the same time,we also expand the application of information dissemination model in strengthening information diffusion and public opinion control.Therefore,the research of this paper will greatly enrich and deepen our theoretical cognition and technical methods of social network structure and information interaction,and it is great significance to promote the establishment and improvement of information communication theory.First,understanding of the evolutionary mechanism of online social networks is greatly significant for the development of network science,but up to now most present researches on this topic have not enough insight.In this study,firstly we empirically showed the essential evolution characteristics of Renren online social network.The evolution mechanism of online social networks is explained by the perspective of Pareto wealth distribution and bidirectional preferential attachment.Then a novel model is proposed to reproduce the evolution characteristics which are consistent with the ones of Renren online social network.The results suggest that both Pareto wealth distribution and bidirectional preferential attachment play an important role in the evolution process of online social networks and can help us to understand the evolutionary origin of online social networks.Second,degree assortativity characterizes the propensity for large-degree nodes to connect to other large-degree nodes and low-degree to low-degree.To understand the evolutionary dynamics of degree assortativity,we collect a variety of empirical temporal social networks,and find that there is a universal pattern that the degree assortativity increases at the beginning of evolution and then decreases to a long-lasting stable level.We develop a bidirectional selection model to re-construct the evolution dynamic.By varying the ratio of link establishment from within the same status level to across different status levels,the simulated network can be tuned to be assortative or disassortative.This suggests that the rise-and-fall pattern of degree assortativity is a consequence of the different network-forming forces active at different mixing of status.Our simulations indicate that Pareto social status distribution in the population may drive the social evolution in a way of self-optimization to promote the social interaction among individuals and the status gap plays an important role for the assortativity of the social network.Finally,the research on the information interaction mechanism of the mobile communication networks is great significant for understanding the human communication pattern.In this paper,a mobile communication network is constructed from the mobile phone call records of one specific city in China.We assign one weight on each edge to reflect the strength of social tie,which is the cumulative number of calls placed between the individuals.The experimental results of the weight distribution follow a power-law.In the mobile communication network with strong tie,the degree distribution also follows a power-law.From the perspective of the information interaction between individuals,the evolution mechanism of the mobile communication networks is given to explain the logical relation between the information interaction and the topology structure.Then a novel model based on the evolution mechanism is proposed to reproduce the topology characteristics of the mobile communication network.The model can help us to understand the law of the human information interaction and has significant implications for dynamic simulation researches of social networks,especially in information diffusion through the social networks.