Investigation Of Reliable Information Distribution And Management Mechanisms In Online Social Networks

Online social networks(OSNs)refer to the network structure formed by connecting online entities with different attributes in accordance with certain association rules.OSNs have broken the limit of physical space and geology,showing the potential to become large scale.The prevalence and development of the Internet and new communication technology have provided convenience for the development of OSNs.In modern era of information,the Internet has become one of the core channels for access to information.Correspondingly,the OSNs have also played a significant role in information production,dissemination and distribution.With the continuous development of the Internet,the scale of OSNs has also shown an exponential growth trend.Large network scale results in the explosive amount of information generated and spread in the network.However,the enormous amount of information has led to the decline of information quality.Due to the imperfection of information audit technology,certain amount of negative information has been generated and spread in network,which challenges the information security of the network space.Therefore,it is of great theoretical and practical importance to investigate the reliable distribution strategy of information in OSNs.The reliable distribution of information requires effective intervention in the process of information propagation based on the topological structure of the network.Hence,it is necessary to study the propagation mechanism of information in OSNs.It is notable that the mechanism of information propagation in real world OSNs is very complicated,which is difficult to describe accurately by a single model.In other words,a comprehensive model needs to be studied from multiple levels and perspectives.When information can be distributed and propagated reliably in an OSN,it will create certain information influence.The effective evaluation and management of this influence is significant for the future development direction of the network.Based on above analysis,this thesis studies the following three aspects: the study of information propagation mechanism in OSNs,the study of reliable information distribution strategies especially for negative information propagation in OSNs,and the efficient management methods for information influence in OSNs.The concrete research contents are as follows:Firstly,the study of information diffusion mechanism in online social networks.Information propagation studies the mechanism of spontaneous diffusion of information between nodes in a network,and is the foundation of designing effective information distribution strategy.The mechanism of realistic information dissemination is complicated,which most researches can only explain from a single perspective.This thesis first collects and analyzes real-world information propagation data,and proposes a novel macro-perspective diffusion model based on Chi Square distribution to predict the global propagation intensity;then,by extracting one sub-cascade from information diffusion,this thesis proposes a micro-perspective diffusion model based on Simulated Annealing mechanism to predict the propagation probability between any pair of nodes in network.Finally,this thesis presents a mixed information diffusion model based on Ising model.By combining this mixed information diffusion mode with Survival Theory,our proposed method can calculate the global information diffusion probability over the entire network and more accurately predict information diffusion trend and influence.Secondly,the study of reliable information distribution strategies.Information security has become one of the major issues in online social network space.For the negative information(such as false news or rumors),it is significant to present reliable distribution strategies.This thesis first optimizes the information diffusion pattern by fitting real-world data with proper probability distribution function,with which this thesis calculates the global information diffusion probability for any pre-defined time period.Then this thesis formulates this global diffusion probability as the objective function of blocking strategy.Meanwhile,in order to satisfy certain network Quality of Service constraint,this thesis proposes a user experience utility function as a constraint of designing blocking strategy.Finally,based on classic Greedy algorithm,this thesis presents both static and dynamic blocking algorithms to select a certain number of key nodes in an online social network to block,so as to achieve the goal of limiting the negative influence and implementing reliable information distribution.Thirdly,the study of efficient information management methods.Information spreads and distributes in OSNs will create certain influence and how to effectively evaluate and manage the influence is significant for network development.Academic cooperations are of tremendous importance for technology innovating.Therefore,this thesis studies the information management strategies in academic online social network formed by academic cooperations.This thesis focuses on the online social network based on academic cooperations between different academic affiliations.A multi-graph is utilized to describe the cooperations in different years for different affiliations.Then,according to information entropy theory,this thesis establishes diverse evaluation indexes for academic cooperations.Hopefully,these strategies can provide valuable information for the development of network.Finally,we summarize the research structure and contents of this thesis and analyze the innovation points in it.Furthermore,we also investigate the shortcomings and issues in our current research and make the future study direction and corresponding plan.