Indirect influence in social networks as an induced percolation phenomenon

Xie, Jiarong1; Wang, Xiangrong2,3; Feng, Ling4,5; Zhao, Jin-Hua6,7; Liu, Wenyuan8; Moreno, Yamir9,10,11; Hu, Yanqing12

2022-03-01

10.1073/pnas.2100151119

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA   影响因子和分区

0027-8424

1091-6490

Percolation theory has been widely used to study phase transitions in network systems. It has also successfully explained various macroscopic spreading phenomena across different fields. Yet, the theoretical frameworks have been focusing on direct interactions among nodes, while recent empirical observations have shown that indirect interactions are common in many network systems like social and ecological networks, among others. By investigating the detailed mechanism of both direct and indirect influence on scientific collaboration networks, here we show that indirect influence can play the dominant role in behavioral influence. To address the lack of theoretical understanding of such indirect influence on the macroscopic behavior of the system, we propose a percolation mechanism of indirect interactions called induced percolation. Surprisingly, our model exhibits a unique anisotropy property. Specifically, directed networks show first-order abrupt transitions as opposed to the second-order continuous transition in the same network structure but with undirected links. A mix of directed and undirected links leads to rich hybrid phase transitions. Furthermore, a unique feature of the nonmonotonic pattern is observed in network connectivities near the critical point. We also present an analytical framework to characterize the proposed induced percolation, paving the way to further understanding network dynamics with indirect interactions.

percolation indirect interactions social network phase transition behavioral contagion

SCI

英语

NI论文

通讯

Young TopNotch Talents in Technological Innovation[2019TQ05X138] ; Natural Science Foundation of Guangdong for Distinguished Youth Scholar, Guangdong Provincial Department of Science and Technology[2020B1515020052] ; National Natural Science Foundation of China[61903385,62003156] ; Guangdong Major Project of Basic and Applied Basic Research[2020B0301030008] ; Chinese Academy of Sciences[QYZDJ-SSW-SYS018]

Science & Technology - Other Topics

Multidisciplinary Sciences

WOS:000766705700002

NATL ACAD SCIENCES

BIOLOGY & BIOCHEMISTRY;CLINICAL MEDICINE;MULTIDISCIPLINARY;PLANT & ANIMAL SCIENCE;ENVIRONMENT/ECOLOGY;SOCIAL SCIENCES, GENERAL;MICROBIOLOGY;ECONOMICS BUSINESS;IMMUNOLOGY;MATERIALS SCIENCE;MATHEMATICS;SPACE SCIENCE;MOLECULAR BIOLOGY & GENETICS;PHARMACOLOGY & TOXICOLOGY;CHEMISTRY;PSYCHIATRY/PSYCHOLOGY;NEUROSCIENCE & BEHAVIOR;PHYSICS;GEOSCIENCES;AGRICULTURAL SCIENCES;ENGINEERING

Web of Science

1.Sun Yat Sen Univ, Sch Comp Sci & Engn, Guangzhou 510006, Peoples R China
2.Southern Univ Sci & Technol, Inst Future Networks, Shenzhen 518055, Peoples R China
3.Peng Cheng Lab, Shenzhen 518066, Peoples R China
4.ASTAR, Inst High Performance Comp, Singapore 138632, Singapore
5.Natl Univ Singapore, Dept Phys, Singapore 117551, Singapore
6.South China Normal Univ, Inst Quantum Matter, Guangdong Prov Key Lab Nucl Sci, Guangzhou 510006, Peoples R China
7.South China Normal Univ, Southern Nucl Sci Comp Ctr, Guangdong Hong Kong Joint Lab Quantum Matter, Guangzhou 510006, Peoples R China
8.Nanyang Technol Univ, Sch Phys & Math Sci, Div Phys & Appl Phys, Singapore 637371, Singapore
9.Univ Zaragoza, Inst Biocomputat & Phys Complex Syst, Zaragoza 50018, Spain
10.Univ Zaragoza, Dept Theoret Phys, Zaragoza 50018, Spain
11.ISI Fdn, I-10126 Turin, Italy
12.Southern Univ Sci & Technol, Coll Sci, Dept Stat & Data Sci, Shenzhen 518055, Peoples R China

Xie, Jiarong,Wang, Xiangrong,Feng, Ling,et al. Indirect influence in social networks as an induced percolation phenomenon[J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA,2022,119(9).

Xie, Jiarong.,Wang, Xiangrong.,Feng, Ling.,Zhao, Jin-Hua.,Liu, Wenyuan.,...&Hu, Yanqing.(2022).Indirect influence in social networks as an induced percolation phenomenon.PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA,119(9).

Xie, Jiarong,et al."Indirect influence in social networks as an induced percolation phenomenon".PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 119.9(2022).