Exposure And Reinforcement Of Information Diffusion In Large-scale Online Social Networks

With the rapid development of network,the fast popularization of mobile terminal,and the frequent information interaction between users,the information redundancy has gradually attracted the attention of many researchers.On the one hand,repeated information sharing and forwarding reduce the users' experience of using the platform;On the other hand,peer influence and social reinforcement effect between users also provide the possibility for information diffusion and influence maximization.This thesis focuses on the information redundancy in online social platforms,and the coverage and reinforcement effects in the process of information dissemination,and the works of this thesis are summarized as follows:(1)This paper first describes the redundancy phenomenon in online social media,define the exposure and re-exposure rate in the process of information diffusion,and propose a redundancy model.(2)The analytical value of the probability that nodes are covered repeatedly in the process of information transmission is approximated.(3)Based on the simulation experiment,the relationship between network structure and redundancy rate is analyzed.(4)In order to increase the reliability of the model,50 trending topics in Chinese large social platform Sina Weibo are collected to verify the simulation results,characteristics and diffusion mechanism of redundant information are investigated by empirical data.(5)Considering the information delivery strategy,this study design the information delivery strategy for different diffusion goals,which lay a good foundation and provides a strong quantitative analysis support for information intelligence propaganda,network information confrontation,and enterprises to develop scientific and accurate marketing programs..The results show that the probability of nodes being covered repeatedly in the process of information transmission can be described and depicted accurately by mathematical expressions.Network characteristic,as well as the transmission pathways are critical for the two metrics to be optimized.The bringing in of re-exposure rate when studying information spreading also shell light on the examination of user behavioral patterns,such as to help identification of commercial users or social bots through information transmission pathways and coverage.Alongside these key findings,we have also identified a few representative strategies which may be implemented to minimize or maximize dual influence,such perspectives of modeling would undoubtedly make nowadays marketing to be reformulated.The study provides a new perspective for understanding the characteristics of information diffusion,helps to understand the impact of network structure on information dissemination,and has certain theoretical and practical significance for grasping the law of information dissemination,redundant information characteristics,public opinion analysis on social platforms,and others.