IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v499y2018icp121-128.html
   My bibliography  Save this article

Social contagions on correlated multiplex networks

Author

Listed:
  • Wang, Wei
  • Cai, Meng
  • Zheng, Muhua

Abstract

The existence of interlayer degree correlations has been disclosed by abundant multiplex network analysis. However, how they impose on the dynamics of social contagions are remain largely unknown. In this paper, we propose a non-Markovian social contagion model in multiplex networks with inter-layer degree correlations to delineate the behavior spreading, and develop an edge-based compartmental (EBC) theory to describe the model. We find that multiplex networks promote the final behavior adoption size. Remarkably, it can be observed that the growth pattern of the final behavior adoption size, versus the behavioral information transmission probability, changes from discontinuous to continuous once decreasing the behavior adoption threshold in one layer. We finally unravel that the inter-layer degree correlations play a role on the final behavior adoption size but have no effects on the growth pattern, which is coincidence with our prediction by using the suggested theory.

Suggested Citation

  • Wang, Wei & Cai, Meng & Zheng, Muhua, 2018. "Social contagions on correlated multiplex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 121-128.
    • Handle: RePEc:eee:phsmap:v:499:y:2018:i:c:p:121-128
    DOI: 10.1016/j.physa.2017.12.081
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437117313304
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2017.12.081?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Réka Albert & Hawoong Jeong & Albert-László Barabási, 2000. "Error and attack tolerance of complex networks," Nature, Nature, vol. 406(6794), pages 378-382, July.
    2. Sergey V. Buldyrev & Roni Parshani & Gerald Paul & H. Eugene Stanley & Shlomo Havlin, 2010. "Catastrophic cascade of failures in interdependent networks," Nature, Nature, vol. 464(7291), pages 1025-1028, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhang, Tianqiao & Zhang, Yang & Zhu, Xuzhen & Chen, Junliang, 2019. "Cascading failures on interdependent networks with star dependent links," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    2. Zhou, Rong & Wu, Qingchu, 2019. "Epidemic spreading dynamics on complex networks with adaptive social-support," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 778-787.
    3. Chen, Ling-Jiao & Chen, Xiao-Long & Cai, Meng & Wang, Wei, 2018. "Complex contagions with social reinforcement from different layers and neighbors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 516-525.
    4. Ren, Bo & Li, Huajiao & Shi, Jianglan & Liu, Yanxin & Qi, Yajie, 2022. "Identifying the key sectors and paths of the embodied energy in BRICS nations: A weighted multilayer network approach," Energy, Elsevier, vol. 239(PB).
    5. Chow, Sheung Chi & Vieito, João Paulo & Wong, Wing Keung, 2019. "Do both demand-following and supply-leading theories hold true in developing countries?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 536-554.
    6. Zhang, Gui-Qing & Baró, Jordi & Cheng, Fang-Yin & Huang, He & Wang, Lin, 2019. "Avalanche dynamics of a generalized earthquake model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1463-1471.
    7. Chen, Ning & Zhu, Xuzhen & Chen, Yanyan, 2019. "Information spreading on complex networks with general group distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 671-676.
    8. Zhu, Shu-Shan & Zhu, Xu-Zhen & Wang, Jian-Qun & Zhang, Zeng-Ping & Wang, Wei, 2019. "Social contagions on multiplex networks with heterogeneous population," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 105-113.
    9. Zhang, Yaming & Su, Yanyuan & Weigang, Li & Liu, Haiou, 2019. "Interacting model of rumor propagation and behavior spreading in multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 121(C), pages 168-177.
    10. Lu, Yao & Chen, Yanyan & Xiong, Jie & Chen, Ning & Zhou, Bin & Zhu, Xuzhen, 2019. "Effects of group size distribution on cascading failure in partially interdependent networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    11. Zou, Yang & Xiong, Zhongyang & Zhang, Pu & Wang, Wei, 2018. "Social contagions on multiplex networks with different reliability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 728-735.
    12. Zhang, Shuang & Wang, Wei & Wu, Tao & Lin, Tao, 2019. "Phase transition of a generalized contact process on complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    13. Wang, Jian & Fang, Hongying & Qin, Xiaolin, 2019. "Targeted attack on correlated interdependent networks with dependency groups," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    14. Yi, Yinxue & Zhang, Zufan & Gan, Chenquan, 2018. "The effect of social tie on information diffusion in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 783-794.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chen, Lei & Yue, Dong & Dou, Chunxia, 2019. "Optimization on vulnerability analysis and redundancy protection in interdependent networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1216-1226.
    2. Deng, Ye & Wu, Jun & Tan, Yue-jin, 2016. "Optimal attack strategy of complex networks based on tabu search," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 74-81.
    3. Wang, Jianwei & Cai, Lin & Xu, Bo & Li, Peng & Sun, Enhui & Zhu, Zhiguo, 2016. "Out of control: Fluctuation of cascading dynamics in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 1231-1243.
    4. Zhou, Yaoming & Wang, Junwei, 2018. "Efficiency of complex networks under failures and attacks: A percolation approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 658-664.
    5. Wang, Weihong & Chen, MingMing & Min, Yong & Jin, Xiaogang, 2016. "Structural diversity effects of multilayer networks on the threshold of interacting epidemics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 254-262.
    6. Khakzad, Nima & Reniers, Genserik & Abbassi, Rouzbeh & Khan, Faisal, 2016. "Vulnerability analysis of process plants subject to domino effects," Reliability Engineering and System Safety, Elsevier, vol. 154(C), pages 127-136.
    7. Liu, Run-Ran & Chu, Changchang & Meng, Fanyuan, 2023. "Higher-order interdependent percolation on hypergraphs," Chaos, Solitons & Fractals, Elsevier, vol. 177(C).
    8. Rui Peng & Di Wu & Mengyao Sun & Shaomin Wu, 2021. "An attack-defense game on interdependent networks," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 72(10), pages 2331-2341, October.
    9. Zhu, Qian & Zhu, Zhiliang & Wang, Yifan & Yu, Hai, 2016. "Fuzzy-information-based robustness of interconnected networks against attacks and failures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 458(C), pages 194-203.
    10. Wouter Vermeer & Otto Koppius & Peter Vervest, 2018. "The Radiation-Transmission-Reception (RTR) model of propagation: Implications for the effectiveness of network interventions," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-21, December.
    11. Lu, Qing-Chang & Xu, Peng-Cheng & Zhao, Xiangmo & Zhang, Lei & Li, Xiaoling & Cui, Xin, 2022. "Measuring network interdependency between dependent networks: A supply-demand-based approach," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    12. Gangwal, Utkarsh & Singh, Mayank & Pandey, Pradumn Kumar & Kamboj, Deepak & Chatterjee, Samrat & Bhatia, Udit, 2022. "Identifying early-warning indicators of onset of sudden collapse in networked infrastructure systems against sequential disruptions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 591(C).
    13. Wang, Jianwei & Jiang, Chen & Qian, Jianfei, 2014. "Robustness of interdependent networks with different link patterns against cascading failures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 393(C), pages 535-541.
    14. Jin-Hee Cho & Jianxi Gao, 2016. "Cyber War Game in Temporal Networks," PLOS ONE, Public Library of Science, vol. 11(2), pages 1-16, February.
    15. Hayato Goto & Hideki Takayasu & Misako Takayasu, 2017. "Estimating risk propagation between interacting firms on inter-firm complex network," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-12, October.
    16. Jalili, Mahdi, 2011. "Error and attack tolerance of small-worldness in complex networks," Journal of Informetrics, Elsevier, vol. 5(3), pages 422-430.
    17. Liu, Hao & Chen, Xin & Huo, Long & Zhang, Yadong & Niu, Chunming, 2022. "Impact of inter-network assortativity on robustness against cascading failures in cyber–physical power systems," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    18. Jiang, Zhong-Yuan & Zeng, Yong & Liu, Zhi-Hong & Ma, Jian-Feng, 2019. "Identifying critical nodes’ group in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 121-132.
    19. Jordán, Ferenc, 2022. "The network perspective: Vertical connections linking organizational levels," Ecological Modelling, Elsevier, vol. 473(C).
    20. Wang, Weiping & Yang, Saini & Hu, Fuyu & Stanley, H. Eugene & He, Shuai & Shi, Mimi, 2018. "An approach for cascading effects within critical infrastructure systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 164-177.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:499:y:2018:i:c:p:121-128. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.