Topological phase transition in network spreading

作     者：年福忠 张霞 Fuzhong Nian;Xia Zhang

作者机构：School of Computer&CommunicationLanzhou University of TechnologyLanzhou 730050China 

出 版 物：《Chinese Physics B》 (中国物理B（英文版）)

年 卷 期：2023年第32卷第3期

页      面：629-641页

核心收录：

学科分类：07[理学] 070104[理学-应用数学] 0701[理学-数学] 

基　　金：the National Natural Science Foundation of China(Grant Nos.61863025 and 62266030) Program for International S&T Cooperation Projects of Gansu Province of China(Grant No.144WCGA166) Program for Longyuan Young Innovation Talents and the Doctoral Foundation of LUT 

主　　题：social network information spreading network structure phase transition 

摘      要：This paper investigates information spreading from the perspective of topological phase ***,a new hybrid network is constructed based on the small-world networks and scale-free ***,the attention mechanism of online users in information spreading is studied from four aspects:social distance,individual influence,content richness,and individual activity,and a dynamic evolution model of connecting with spreading is ***,numerical simulations are conducted in three types of networks to verify the validity of the proposed dynamic evolution *** simulation results show that topological structure and node influence in different networks have undergone phase transition,which is consistent with the phenomenon that followers and individual influence in real social networks experience phase transition within a short *** infection density of networks with the dynamic evolution rule changes faster and reaches higher values than that of networks without the dynamic evolution ***,the simulation results are compared with the real data,which shows that the infection density curve of the hybrid networks is closer to that of the real data than that of the small-world networks and scale-free networks,verifying the validity of the model proposed in this paper.