IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v534y2019ics0378437119311628.html
   My bibliography  Save this article

Spreading dynamics of SVFR online fraud information model on heterogeneous networks

Author

Listed:
  • Hou, Jingrui
  • Chi, Ming
  • Li, Tao
  • Guan, Zhi-Hong
  • Luo, Kai
  • Zhang, Ding-Xue

Abstract

In recent years, with the development of Internet technology, online fraud has become rampant. Therefore, it is necessary to study its spreading and evolution mechanism. In this paper, we propose a novel susceptible individuals–victims–fraudsters–resisters (SVFR) online fraud information spreading model based on scale-free networks. Using the mean-field theory, we derive the basic reproduction number R0 and prove that when R0<1, the online fraud will disappear eventually, and when R0>1, the online fraud will persist. The stability analysis of our model is also given in detail. Numerical simulations are presented to verify and extend theoretical results. Furthermore, we give four control strategies of online fraud and compare the feasibility and effect of them through some simulations. Finally, we carry on a questionnaire survey to make a further practical exploration.

Suggested Citation

  • Hou, Jingrui & Chi, Ming & Li, Tao & Guan, Zhi-Hong & Luo, Kai & Zhang, Ding-Xue, 2019. "Spreading dynamics of SVFR online fraud information model on heterogeneous networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    • Handle: RePEc:eee:phsmap:v:534:y:2019:i:c:s0378437119311628
    DOI: 10.1016/j.physa.2019.122026
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437119311628
    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.2019.122026?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. Liu, Xiongding & Li, Tao & Xu, Hao & Liu, Wenjin, 2019. "Spreading dynamics of an online social information model on scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 497-510.
    2. Xu, Hao & Li, Tao & Liu, Xiongding & Liu, Wenjin & Dong, Jing, 2019. "Spreading dynamics of an online social rumor model with psychological factors on scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 234-246.
    3. Liu, Qiming & Li, Tao & Sun, Meici, 2017. "The analysis of an SEIR rumor propagation model on heterogeneous network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 372-380.
    4. Wan, Chen & Li, Tao & Guan, Zhi-Hong & Wang, Yuanmei & Liu, Xiongding, 2017. "Spreading dynamics of an e-commerce preferential information model on scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 192-200.
    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. Cuixia Jiang & Jun Zhu & Qifa Xu, 2022. "Dissecting click farming on the Taobao platform in China via PU learning and weighted logistic regression," Electronic Commerce Research, Springer, vol. 22(1), pages 157-176, March.
    2. Dong, Xuefan & Lian, Ying, 2021. "A review of social media-based public opinion analyses: Challenges and recommendations," Technology in Society, Elsevier, vol. 67(C).

    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. Ding, Haixin & Xie, Li, 2023. "Simulating rumor spreading and rebuttal strategy with rebuttal forgetting: An agent-based modeling approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 612(C).
    2. Yanhui Wei & Liang’an Huo & Hongguang He, 2022. "Research on Rumor-Spreading Model with Holling Type III Functional Response," Mathematics, MDPI, vol. 10(4), pages 1-13, February.
    3. Yin, Fulian & Jiang, Xinyi & Qian, Xiqing & Xia, Xinyu & Pan, Yanyan & Wu, Jianhong, 2022. "Modeling and quantifying the influence of rumor and counter-rumor on information propagation dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
    4. Chen, Shanshan & Jiang, Haijun & Li, Liang & Li, Jiarong, 2020. "Dynamical behaviors and optimal control of rumor propagation model with saturation incidence on heterogeneous networks," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    5. Huo, Liang’an & Chen, Sijing, 2020. "Rumor propagation model with consideration of scientific knowledge level and social reinforcement in heterogeneous network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 559(C).
    6. Cheng, Yingying & Huo, Liang’an & Zhao, Laijun, 2020. "Rumor spreading in complex networks under stochastic node activity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 559(C).
    7. Fu, Minglei & Feng, Jun & Lande, Dmytro & Dmytrenko, Oleh & Manko, Dmytro & Prakapovich, Ryhor, 2021. "Dynamic model with super spreaders and lurker users for preferential information propagation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 561(C).
    8. Xu, Hao & Li, Tao & Liu, Xiongding & Liu, Wenjin & Dong, Jing, 2019. "Spreading dynamics of an online social rumor model with psychological factors on scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 234-246.
    9. Hosni, Adil Imad Eddine & Li, Kan & Ahmad, Sadique, 2020. "Analysis of the impact of online social networks addiction on the propagation of rumors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    10. Yanlan Mei & Yan Tu & Kefan Xie & Yicheng Ye & Wenjing Shen, 2019. "Internet Public Opinion Risk Grading under Emergency Event Based on AHPSort II-DEMATEL," Sustainability, MDPI, vol. 11(16), pages 1-16, August.
    11. Li, Dandan & Qian, Wenqi & Sun, Xiaoxiao & Han, Dun & Sun, Mei, 2023. "Rumor spreading in a dual-relationship network with diverse propagation abilities," Applied Mathematics and Computation, Elsevier, vol. 458(C).
    12. Meihui Jiang, 2022. "Locating the Principal Sectors for Carbon Emission Reduction on the Global Supply Chains by the Methods of Complex Network and Susceptible–Infective Model," Sustainability, MDPI, vol. 14(5), pages 1-13, February.
    13. Huo, Liang’an & Cheng, Yingying & Liu, Chen & Ding, Fan, 2018. "Dynamic analysis of rumor spreading model for considering active network nodes and nonlinear spreading rate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 24-35.
    14. Ke, Yue & Zhu, Linhe & Wu, Peng & Shi, Lei, 2022. "Dynamics of a reaction-diffusion rumor propagation model with non-smooth control," Applied Mathematics and Computation, Elsevier, vol. 435(C).
    15. Wu, Jie & Deng, Qun & Han, Tao & Yang, Qing-Sheng & Zhan, Heng, 2019. "Bipartite tracking consensus for multi-agent systems with Lipschitz-Type nonlinear dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1360-1369.
    16. Huo, Liang’an & Cheng, Yingying, 2019. "Dynamical analysis of a IWSR rumor spreading model with considering the self-growth mechanism and indiscernible degree," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    17. Lan, Yuexin & Lian, Zhixuan & Zeng, Runxi & Zhu, Di & Xia, Yixue & Liu, Mo & Zhang, Peng, 2020. "A statistical model of the impact of online rumors on the information quantity of online public opinion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).
    18. Shan Gao & Ye Zhang & Wenhui Liu, 2021. "How Does Risk-Information Communication Affect the Rebound of Online Public Opinion of Public Emergencies in China?," IJERPH, MDPI, vol. 18(15), pages 1-14, July.
    19. Huo, Liang’an & Ding, Fan & Cheng, Yingying, 2019. "Dynamic analysis of a SIbInIu, rumor spreading model in complex social network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 924-932.
    20. Zhu, Linhe & Liu, Wenshan & Zhang, Zhengdi, 2020. "Delay differential equations modeling of rumor propagation in both homogeneous and heterogeneous networks with a forced silence function," Applied Mathematics and Computation, Elsevier, vol. 370(C).

    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:534:y:2019:i:c:s0378437119311628. 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.