Indirect influence in social networks as an induced percolation phenomenon-Reference-Cited by-同舟云学术

Indirect influence in social networks as an induced percolation phenomenon

Published:2022-02-25 Issue:9 Volume:119 Page:
ISSN:0027-8424
Container-title:Proceedings of the National Academy of Sciences
language:en
Short-container-title:Proc. Natl. Acad. Sci. U.S.A.

Author:

Xie Jiarong¹^ORCID,Wang Xiangrong²³^ORCID,Feng Ling⁴⁵^ORCID,Zhao Jin-Hua⁶⁷^ORCID,Liu Wenyuan⁸,Moreno Yamir⁹¹⁰¹¹^ORCID,Hu Yanqing¹²

Affiliation:

1. School of Computer Science and Engineering, Sun Yat-sen University, 510006 Guangzhou, China

2. Institute of Future Networks, Southern University of Science and Technology, 518055 Shenzhen, China

3. Peng Cheng Laboratory, 518066 Shenzhen, China

4. Institute of High Performance Computing, A*STAR, 138632 Singapore

5. Department of Physics, National University of Singapore, 117551 Singapore

6. Guangdong Provincial Key Laboratory of Nuclear Science, Institute of Quantum Matter, South China Normal University, 510006 Guangzhou, China

7. Guangdong-Hong Kong Joint Laboratory of Quantum Matter, Southern Nuclear Science Computing Center, South China Normal University, 510006 Guangzhou, China

8. Division of Physics and Applied Physics, School of Physical and Mathematical Sciences, Nanyang Technological University, 637371 Singapore

9. Institute for Biocomputation and Physics of Complex Systems, University of Zaragoza, 50018 Zaragoza, Spain

10. Department of Theoretical Physics, University of Zaragoza, 50018 Zaragoza, Spain

11. ISI Foundation, 10126 Torino, Italy

12. Department of Statistics and Data Science, College of Science, Southern University of Science and Technology, 518055 Shenzhen, China

Abstract

Significance Increasing empirical evidence in diverse social and ecological systems has shown that indirect interactions play a pivotal role in shaping systems’ dynamical behavior. Our empirical study on collaboration networks of scientists further reveals that an indirect effect can dominate over direct influence in behavioral spreading. However, almost all models in existence focus on direct interactions, and the general impact of indirect interactions has not been studied. We propose a new percolation process, termed induced percolation, to characterize indirect interactions and find that indirect interactions raise a plethora of new phenomena, including the wide range of possible phase transitions. Such an indirect mechanism leads to very different spreading outcomes from that of direct influences.

Funder

The national natural science foundation of China

Publisher

Proceedings of the National Academy of Sciences

Subject

Multidisciplinary

Link

https://pnas.org/doi/pdf/10.1073/pnas.2100151119

Reference45 articles.

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