IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v10y2022i18p3265-d910148.html
   My bibliography  Save this article

Hybrid Fake Information Containing Strategy Exploiting Multi-Dimensions Data in Online Community

Author

Listed:
  • Huiru Cao

    (Department of Information Engineering, Guangzhou Institute of Technology, Guangzhou 510725, China)

  • Xiaomin Li

    (College of Mechanical and Electrical Engineering, Zhongkai University of Agriculture and Engineering, Guangzhou 510225, China)

  • Yanfeng Lin

    (College of Mechanical and Electrical Engineering, Zhongkai University of Agriculture and Engineering, Guangzhou 510225, China)

  • Songyao Lian

    (Department of Electrical and Computer Engineering, Nanfang College of Sun Yat-sen University, Guangzhou 510970, China)

Abstract

It is well-established that, in the past few years, internet users have rapidly increased. Meanwhile, various types of fake information (such as fake news or rumors) have been flooding social media platforms or online communities. The effective containing or controlling of fake news or rumor has drawn wide attention from areas such as academia to social media platforms. For that reason, numerous studies have focused on this subject from different perspectives, such as employing complex networks and spreading models. However, in the real online community, misinformation usually spreads quickly to thousands of users within minutes. Conventional studies are too theoretical or complicated to be applied to practical applications, and show a lack of fast responsiveness and poor containing effects. Therefore, in this work, a hybrid strategy exploiting the multi-dimensional data of users and content was proposed for the fast containing of fake information in the online community. The strategy is mainly composed of three steps: the fast detection of fake information by continuously updating the content comparison dataset according to the specific hot topic and the fake contents; creating spreading force models and user divisions via historical data, and limiting the propagation of fake information based on the content and user division. Finally, an experiment was set up online with BBS (Bulletin Board System), and the acquired results were analyzed by comparison with other methods in different metrics. From the extracted results, it has been demonstrated that the proposed solution clearly outperforms traditional methods.

Suggested Citation

  • Huiru Cao & Xiaomin Li & Yanfeng Lin & Songyao Lian, 2022. "Hybrid Fake Information Containing Strategy Exploiting Multi-Dimensions Data in Online Community," Mathematics, MDPI, vol. 10(18), pages 1-13, September.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:18:p:3265-:d:910148
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/10/18/3265/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/10/18/3265/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dong, Gaogao & Luo, Yanting & Liu, Yangyang & Wang, Fan & Qin, Huanmei & Vilela, André L.M., 2022. "Percolation behaviors of a network of networks under intentional attack with limited information," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).
    2. Dietram A. Scheufele & Nicole M. Krause, 2019. "Science audiences, misinformation, and fake news," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 116(16), pages 7662-7669, April.
    Full references (including those not matched with items on IDEAS)

    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. Carlos Carrasco-Farré, 2022. "The fingerprints of misinformation: how deceptive content differs from reliable sources in terms of cognitive effort and appeal to emotions," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-18, December.
    2. James N. Druckman, 2022. "Threats to Science: Politicization, Misinformation, and Inequalities," The ANNALS of the American Academy of Political and Social Science, , vol. 700(1), pages 8-24, March.
    3. Xuhao Shao & Ao Li & Chuansheng Chen & Elizabeth F. Loftus & Bi Zhu, 2023. "Cross-stage neural pattern similarity in the hippocampus predicts false memory derived from post-event inaccurate information," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    4. Li, Ling & Dong, Gaogao & Zhu, Huaiping & Tian, Lixin, 2024. "Impact of multiple doses of vaccination on epidemiological spread in multiple networks," Applied Mathematics and Computation, Elsevier, vol. 472(C).
    5. Philipp Lorenz-Spreen & Stephan Lewandowsky & Cass R. Sunstein & Ralph Hertwig, 2020. "How behavioural sciences can promote truth, autonomy and democratic discourse online," Nature Human Behaviour, Nature, vol. 4(11), pages 1102-1109, November.
    6. Danielle Caled & Mário J. Silva, 2022. "Digital media and misinformation: An outlook on multidisciplinary strategies against manipulation," Journal of Computational Social Science, Springer, vol. 5(1), pages 123-159, May.
    7. Liang, Yuan & Qi, Mingze & Huangpeng, Qizi & Duan, Xiaojun, 2023. "Percolation of interlayer feature-correlated multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
    8. Abayomi Samuel Oyekale, 2021. "Willingness to Take COVID-19 Vaccines in Ethiopia: An Instrumental Variable Probit Approach," IJERPH, MDPI, vol. 18(17), pages 1-11, August.
    9. Juana Farfán & María Elena Mazo, 2021. "Disinformation and Responsibility in Young People in Spain during the COVID-19 Era," Publications, MDPI, vol. 9(3), pages 1-8, August.
    10. Niels G. Mede, 2022. "Legacy media as inhibitors and drivers of public reservations against science: global survey evidence on the link between media use and anti-science attitudes," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-11, December.
    11. Jonathon P. Schuldt & Adam R. Pearson & Neil A. Lewis jr. & Ashley Jardina & Peter K. Enns, 2022. "Inequality and Misperceptions of Group Concerns Threaten the Integrity and Societal Impact of Science," The ANNALS of the American Academy of Political and Social Science, , vol. 700(1), pages 195-207, March.
    12. Lee, Edmund W.J. & Bao, Huanyu & Wang, Yixi & Lim, Yi Torng, 2023. "From pandemic to Plandemic: Examining the amplification and attenuation of COVID-19 misinformation on social media," Social Science & Medicine, Elsevier, vol. 328(C).
    13. Hu, Xinlei & Huang, Jie & Shi, Feng, 2022. "A robustness assessment with passenger flow data of high-speed rail network in China," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).
    14. Alberto Barchetti & Emma Neybert & Susan Powell Mantel & Frank R. Kardes, 2022. "The Half-Truth Effect and Its Implications for Sustainability," Sustainability, MDPI, vol. 14(11), pages 1-19, June.
    15. Kaisu Koivumäki & Timo Koivumäki & Erkki Karvonen, 2020. "“On Social Media Science Seems to Be More Human”: Exploring Researchers as Digital Science Communicators," Media and Communication, Cogitatio Press, vol. 8(2), pages 425-439.
    16. Jiexun Li & Xiaohui Chang, 2023. "Combating Misinformation by Sharing the Truth: a Study on the Spread of Fact-Checks on Social Media," Information Systems Frontiers, Springer, vol. 25(4), pages 1479-1493, August.
    17. Yunjuan Luo & Yang Cheng, 2021. "The Presumed Influence of COVID-19 Misinformation on Social Media: Survey Research from Two Countries in the Global Health Crisis," IJERPH, MDPI, vol. 18(11), pages 1-15, May.
    18. Gerrath, Maximilian H.E.E. & Olya, Hossein & Shah, Zahra & Li, Huaiyu, 2024. "Virtual influencers and pro-environmental causes: The roles of message warmth and trust in experts," Journal of Business Research, Elsevier, vol. 175(C).
    19. Beniamino Schiavone & Andrea Vitale & Mena Gallo & Gianlucasalvatore Russo & Domenico Ponticelli & Mario Borrelli, 2021. "Overview of Facebook Use by Hospitals in Italy: A Nationwide Survey during the COVID-19 Emergency," IJERPH, MDPI, vol. 18(14), pages 1-17, July.
    20. Peter D. Gluckman & Anne Bardsley & Matthias Kaiser, 2021. "Brokerage at the science–policy interface: from conceptual framework to practical guidance," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-10, December.

    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:gam:jmathe:v:10:y:2022:i:18:p:3265-:d:910148. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.