Evolutionary Computation in Social Propagation over Complex Networks: A Survey

作     者：Tian-Fang Zhao Wei-Neng Chen Xin-Xin Ma Xiao-Kun Wu Tian-Fang Zhao;Wei-Neng Chen;Xin-Xin Ma;Xiao-Kun Wu

作者机构：School of Computer Science&EngineeringSouth China University of TechnologyGuangzhou 510006China School of Journalism and CommunicationSouth China University of TechnologyGuangzhou 510006China 

出 版 物：《International Journal of Automation and computing》 (国际自动化与计算杂志（英文版）)

年 卷 期：2021年第18卷第4期

页      面：503-520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：by National Key Research and Development Project,Ministry of Science and Technology,China(No.2018AAA0101300) National Natural Science Foundation of China(Nos.61976093 and 61873097) Guangdong-Hong Kong Joint Innovative Platform of Big Data and Computational Intelligence(No.2018B050502006) Guangdong Natural Science Foundation Research Team(No.2018B030312003) 

主　　题：Evolutionary computation complex network propagation dynamics social diffusion evolution model optimization algorithm 

摘      要：Social propagation denotes the spread phenomena directly correlated to the human world and society, which includes but is not limited to the diffusion of human epidemics, human-made malicious viruses, fake news, social innovation, viral marketing, etc. Simulation and optimization are two major themes in social propagation, where network-based simulation helps to analyze and understand the social contagion, and problem-oriented optimization is devoted to contain or improve the infection results. Though there have been many models and optimization techniques, the matter of concern is that the increasing complexity and scales of propagation processes continuously refresh the former conclusions. Recently, evolutionary computation(EC) shows its potential in alleviating the concerns by introducing an evolving and developing perspective. With this insight, this paper intends to develop a comprehensive view of how EC takes effect in social propagation. Taxonomy is provided for classifying the propagation problems, and the applications of EC in solving these problems are reviewed. Furthermore, some open issues of social propagation and the potential applications of EC are *** paper contributes to recognizing the problems in application-oriented EC design and paves the way for the development of evolving propagation dynamics.