Complex contagions with social reinforcement from different layers and neighbors

被引:9
|
作者
Chen, Ling-Jiao [1 ,2 ]
Chen, Xiao-Long [1 ,2 ,3 ,4 ]
Cai, Meng [3 ,4 ,5 ]
Wang, Wei [2 ,6 ]
机构
[1] Univ Elect Sci & Technol China, CompleX Lab, Web Sci Ctr, Chengdu 611731, Sichuan, Peoples R China
[2] Univ Elect Sci & Technol China, Big Data Res Ctr, Chengdu 611731, Sichuan, Peoples R China
[3] Boston Univ, Ctr Polymer Studies, Boston, MA 02215 USA
[4] Boston Univ, Dept Phys, Boston, MA 02215 USA
[5] Xidian Univ, Sch Econ & Management, Xian 710071, Shaanxi, Peoples R China
[6] Sichuan Univ, Cybersecur Res Inst, Chengdu 610065, Sichuan, Peoples R China
基金
中国国家自然科学基金;
关键词
Complex networks; Spreading dynamics; Complex contagions;
D O I
10.1016/j.physa.2018.03.017
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
Researches about complex contagions on complex networks always neglect the reinforcement effect from different layers and neighbors simultaneously. In this paper we propose a non-Markovian model to describe complex contagions in which a susceptible node becoming adopted must take the social reinforcement from different layers and neighbors into consideration. Through extensive numerical simulations we find that the final adoption size will increase sharply with the information transmission probability at a large adoption threshold. In addition, for small values of adoption threshold, a few seeds could trigger a global contagion. However, there is a critical seed size below which the global contagion becomes impossible for large values of adoption threshold. Besides that, we develop an edge-based compartmental (EBC) theory to describe the proposed model, and it agrees well with numerical simulations. (C) 2018 Elsevier B.V. All rights reserved.
引用
收藏
页码:516 / 525
页数:10
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