Optimal community structure for social contagions
Community structure is an important factor in the behavior of real-world networks because it strongly affects the stability and thus the phase transition order of the spreading dynamics. We here propose a reversible social contagion model of community networks that includes the factor of social rein...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IOP Publishing
2018-01-01
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| Series: | New Journal of Physics |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/1367-2630/aac0c9 |
| _version_ | 1797750666143203328 |
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| author | Zhen Su Wei Wang Lixiang Li H Eugene Stanley Lidia A Braunstein |
| author_facet | Zhen Su Wei Wang Lixiang Li H Eugene Stanley Lidia A Braunstein |
| author_sort | Zhen Su |
| collection | DOAJ |
| description | Community structure is an important factor in the behavior of real-world networks because it strongly affects the stability and thus the phase transition order of the spreading dynamics. We here propose a reversible social contagion model of community networks that includes the factor of social reinforcement. In our model an individual adopts a social contagion when the number of received units of information exceeds its adoption threshold. We use mean-field approximation to describe our proposed model, and the results agree with numerical simulations. The numerical simulations and theoretical analyses both indicate that there is a first-order phase transition in the spreading dynamics, and that a hysteresis loop emerges in the system when there is a variety of initially adopted seeds. We find an optimal community structure that maximizes spreading dynamics. We also find a rich phase diagram with a triple point that separates the no-diffusion phase from the two diffusion phases. |
| first_indexed | 2024-03-12T16:37:08Z |
| format | Article |
| id | doaj.art-17587d38624a49e4b93443f999a74636 |
| institution | Directory Open Access Journal |
| issn | 1367-2630 |
| language | English |
| last_indexed | 2024-03-12T16:37:08Z |
| publishDate | 2018-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | New Journal of Physics |
| spelling | doaj.art-17587d38624a49e4b93443f999a746362023-08-08T14:49:26ZengIOP PublishingNew Journal of Physics1367-26302018-01-0120505305310.1088/1367-2630/aac0c9Optimal community structure for social contagionsZhen Su0Wei Wang1Lixiang Li2H Eugene Stanley3Lidia A Braunstein4College of Computer Science and Technology, Chongqing University of Posts and Telecommunications , Chongqing 400065, People’s Republic of China; Chongqing MII Key Lab. of Computer Networks & Communications , Chongqing 400065, People’s Republic of ChinaCybersecurity Research Institute, Sichuan University , Chengdu 610065, People’s Republic of ChinaInformation Security Center, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications , Beijing 100876, People’s Republic of ChinaCenter for Polymer Studies and Department of Physics, Boston University , Boston, MA 02215, United States of AmericaCenter for Polymer Studies and Department of Physics, Boston University , Boston, MA 02215, United States of America; Instituto de Investigaciones Físicas de Mar del Plata (IFIMAR)-Departamento de Física, Facultad de Ciencias Exactas y Naturales, Universidad Nacional de Mar del Plata-CONICET , Funes 3350, (7600) Mar del Plata, ArgentinaCommunity structure is an important factor in the behavior of real-world networks because it strongly affects the stability and thus the phase transition order of the spreading dynamics. We here propose a reversible social contagion model of community networks that includes the factor of social reinforcement. In our model an individual adopts a social contagion when the number of received units of information exceeds its adoption threshold. We use mean-field approximation to describe our proposed model, and the results agree with numerical simulations. The numerical simulations and theoretical analyses both indicate that there is a first-order phase transition in the spreading dynamics, and that a hysteresis loop emerges in the system when there is a variety of initially adopted seeds. We find an optimal community structure that maximizes spreading dynamics. We also find a rich phase diagram with a triple point that separates the no-diffusion phase from the two diffusion phases.https://doi.org/10.1088/1367-2630/aac0c9community structuresocial contagionsnonlinear dynamics |
| spellingShingle | Zhen Su Wei Wang Lixiang Li H Eugene Stanley Lidia A Braunstein Optimal community structure for social contagions New Journal of Physics community structure social contagions nonlinear dynamics |
| title | Optimal community structure for social contagions |
| title_full | Optimal community structure for social contagions |
| title_fullStr | Optimal community structure for social contagions |
| title_full_unstemmed | Optimal community structure for social contagions |
| title_short | Optimal community structure for social contagions |
| title_sort | optimal community structure for social contagions |
| topic | community structure social contagions nonlinear dynamics |
| url | https://doi.org/10.1088/1367-2630/aac0c9 |
| work_keys_str_mv | AT zhensu optimalcommunitystructureforsocialcontagions AT weiwang optimalcommunitystructureforsocialcontagions AT lixiangli optimalcommunitystructureforsocialcontagions AT heugenestanley optimalcommunitystructureforsocialcontagions AT lidiaabraunstein optimalcommunitystructureforsocialcontagions |