IDEAS home Printed from https://ideas.repec.org/a/spr/comaot/v27y2021i2d10.1007_s10588-020-09309-6.html
   My bibliography  Save this article

Extent prediction of the information and influence propagation in online social networks

Author

Listed:
  • Raúl M. Ortiz-Gaona

    (Polytechnic University of Catalonia (UPC)
    Universidad de Cuenca)

  • Marcos Postigo-Boix

    (Polytechnic University of Catalonia (UPC))

  • José L. Melús-Moreno

    (Polytechnic University of Catalonia (UPC))

Abstract

We present a new mathematical model that predicts the number of users informed and influenced by messages that are propagated in an online social network. Our model is based on a new way of quantifying the tie-strength, which in turn considers the affinity and relevance between nodes. We could verify that the messages to inform and influence, as well as their importance, produce different propagation behaviors in an online social network. We carried out laboratory tests with our model and with the baseline models Linear Threshold and Independent Cascade, which are currently used in many scientific works. The results were evaluated by comparing them with empirical data. The tests show conclusively that the predictions of our model are notably more accurate and precise than the predictions of the baseline models. Our model can contribute to the development of models that maximize the propagation of messages; to predict the spread of viruses in computer networks, mobile telephony and online social networks.

Suggested Citation

  • Raúl M. Ortiz-Gaona & Marcos Postigo-Boix & José L. Melús-Moreno, 2021. "Extent prediction of the information and influence propagation in online social networks," Computational and Mathematical Organization Theory, Springer, vol. 27(2), pages 195-230, June.
    • Handle: RePEc:spr:comaot:v:27:y:2021:i:2:d:10.1007_s10588-020-09309-6
    DOI: 10.1007/s10588-020-09309-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10588-020-09309-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10588-020-09309-6?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. Samadi, Mohammadreza & Nagi, Rakesh & Semenov, Alexander & Nikolaev, Alexander, 2018. "Seed activation scheduling for influence maximization in social networks," Omega, Elsevier, vol. 77(C), pages 96-114.
    2. António Fonseca & Jorge Louçã, 2018. "Explaining the emergence of online popularity through a model of information diffusion," Computational and Mathematical Organization Theory, Springer, vol. 24(2), pages 169-187, June.
    3. Ning Nan & Robert Zmud & Emre Yetgin, 2014. "A complex adaptive systems perspective of innovation diffusion: an integrated theory and validated virtual laboratory," Computational and Mathematical Organization Theory, Springer, vol. 20(1), pages 52-88, March.
    4. Dustin L. Arendt & Leslie M. Blaha, 2015. "Opinions, influence, and zealotry: a computational study on stubbornness," Computational and Mathematical Organization Theory, Springer, vol. 21(2), pages 184-209, June.
    5. Samadi, Mohammadreza & Nikolaev, Alexander & Nagi, Rakesh, 2016. "A subjective evidence model for influence maximization in social networks," Omega, Elsevier, vol. 59(PB), pages 263-278.
    6. Declan Mungovan & Enda Howley & Jim Duggan, 2011. "The influence of random interactions and decision heuristics on norm evolution in social networks," Computational and Mathematical Organization Theory, Springer, vol. 17(2), pages 152-178, May.
    7. Postigo-Boix, Marcos & Melús-Moreno, José L., 2018. "A social model based on customers’ profiles for analyzing the churning process in the mobile market of data plans," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 571-592.
    8. Sohei Ito & Dominik Vymětal & Roman Šperka & Michal Halaška, 2018. "Process mining of a multi-agent business simulator," Computational and Mathematical Organization Theory, Springer, vol. 24(4), pages 500-531, December.
    9. Alexandra Bekiari & Nikolaos Hasanagas, 2015. "Verbal Aggressiveness Exploration through Complete Social Network Analysis: Using Physical Education Students¡¯ Class as an Illustration," International Journal of Social Science Studies, Redfame publishing, vol. 3(3), pages 30-49, May.
    10. Fan, W. & Yeung, K.H., 2011. "Online social networks—Paradise of computer viruses," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(2), pages 189-197.
    11. Jordi Paniagua & Rafael Rivelles & Juan Sapena, 2019. "Social Determinants of Success: Social Media, Corporate Governance and Revenue," Sustainability, MDPI, vol. 11(19), pages 1-17, September.
    12. Matthew Babcock & Ramon Alfonso Villa Cox & Sumeet Kumar, 2019. "Diffusion of pro- and anti-false information tweets: the Black Panther movie case," Computational and Mathematical Organization Theory, Springer, vol. 25(1), pages 72-84, March.
    13. Shahadat Uddin & Arif Khan & Liaquat Hossain & Mahendra Piraveenan & Sven Carlsson, 2015. "A topological framework to explore longitudinal social networks," Computational and Mathematical Organization Theory, Springer, vol. 21(1), pages 48-68, March.
    14. Hernan Mondani, 2018. "The underlying geometry of organizational dynamics: similarity-based social space and labor flow network communities," Computational and Mathematical Organization Theory, Springer, vol. 24(3), pages 378-400, September.
    15. Bolthausen, Erwin & Wüthrich, Mario V., 2013. "Bernoulli's Law of Large Numbers," ASTIN Bulletin: The Journal of the International Actuarial Association, Cambridge University Press, vol. 43(02), pages 73-79, May.
    16. Qiaoyun Yun & Peter A. Gloor, 2015. "The web mirrors value in the real world: comparing a firm’s valuation with its web network position," Computational and Mathematical Organization Theory, Springer, vol. 21(4), pages 356-379, December.
    17. Rong, Ke & Hu, Guangyu & Lin, Yong & Shi, Yongjiang & Guo, Liang, 2015. "Understanding business ecosystem using a 6C framework in Internet-of-Things-based sectors," International Journal of Production Economics, Elsevier, vol. 159(C), pages 41-55.
    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. Fontecha, John E. & Nikolaev, Alexander & Walteros, Jose L. & Zhu, Zhenduo, 2022. "Scientists wanted? A literature review on incentive programs that promote pro-environmental consumer behavior: Energy, waste, and water," Socio-Economic Planning Sciences, Elsevier, vol. 82(PA).
    2. Jie Ren & Jar-Der Luo & Ke Rong, 2020. "How Do Venture Capitals Build Up Syndication Ecosystems for Sustainable Development?," Sustainability, MDPI, vol. 12(11), pages 1-14, May.
    3. Sophia Barquete & Ana Hiromi Shimozono & Adriana Hofmann Trevisan & Camila Gonçalves Castro & Leonardo Augusto de Vasconcelos Gomes & Janaina Mascarenhas, 2022. "Exploring the Dynamic of a Circular Ecosystem: A Case Study about Drivers and Barriers," Sustainability, MDPI, vol. 14(13), pages 1-22, June.
    4. Hou, Hong & Shi, Yongjiang, 2021. "Ecosystem-as-structure and ecosystem-as-coevolution: A constructive examination," Technovation, Elsevier, vol. 100(C).
    5. Laudien, Sven M. & Reuter, Ute & Sendra Garcia, Francisco Javier & Botella-Carrubi, Dolores, 2024. "Digital advancement and its effect on business model design: Qualitative-empirical insights," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    6. Viktora-Jones, Magdalena & Parente, Ronaldo & Drori, Netanel & Zhao, Yue, 2024. "Firm performance drivers within a dynamic emerging market ecosystem," Journal of International Management, Elsevier, vol. 30(1).
    7. Nihad Faissal Bassis & Fabiano Armellini, 2018. "Systems of innovation and innovation ecosystems: a literature review in search of complementarities," Journal of Evolutionary Economics, Springer, vol. 28(5), pages 1053-1080, December.
    8. Shengyuan Wang, 2022. "Exploring the Sustainability of China’s New Energy Vehicle Development: Fresh Evidence from Population Symbiosis," Sustainability, MDPI, vol. 14(17), pages 1-21, August.
    9. Vincent Leon & S. Rasoul Etesami & Rakesh Nagi, 2022. "Limited-Trust in Diffusion of Competing Alternatives over Social Networks," Papers 2206.06318, arXiv.org, revised Oct 2023.
    10. Li, Pengdeng & Yang, Xiaofan & Yang, Lu-Xing & Xiong, Qingyu & Wu, Yingbo & Tang, Yuan Yan, 2018. "The modeling and analysis of the word-of-mouth marketing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 493(C), pages 1-16.
    11. Mark A. Phillips & Jagjit Singh Srai, 2018. "Exploring Emerging Ecosystem Boundaries: Defining ‘The Game’," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 22(08), pages 1-21, December.
    12. Rong, Ke & Patton, Dean & Chen, Weiwei, 2018. "Business models dynamics and business ecosystems in the emerging 3D printing industry," Technological Forecasting and Social Change, Elsevier, vol. 134(C), pages 234-245.
    13. Liu, Gordon & Aroean, Lukman & Ko, Wai Wai, 2023. "Service innovation in business ecosystem: The roles of shared goals, coopetition, and interfirm power," International Journal of Production Economics, Elsevier, vol. 255(C).
    14. Yanzhang Gu & Longying Hu & Hongjin Zhang & Chenxuan Hou, 2021. "Innovation Ecosystem Research: Emerging Trends and Future Research," Sustainability, MDPI, vol. 13(20), pages 1-21, October.
    15. Florez Ramos, Esmeralda & Blind, Knut, 2020. "Data portability effects on data-driven innovation of online platforms: Analyzing Spotify," Telecommunications Policy, Elsevier, vol. 44(9).
    16. Guannan Xu & Weijie Hu & Yuanyuan Qiao & Yuan Zhou, 2020. "Mapping an innovation ecosystem using network clustering and community identification: a multi-layered framework," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 2057-2081, September.
    17. Youzhong Wang & Daniel Zeng & Bin Zhu & Xiaolong Zheng & Feiyue Wang, 2014. "Patterns of news dissemination through online news media: A case study in China," Information Systems Frontiers, Springer, vol. 16(4), pages 557-570, September.
    18. D׳Souza, Derrick E. & Kulkarni, Shailesh S., 2015. "A framework and model for absorptive capacity in a dynamic multi-firm environment," International Journal of Production Economics, Elsevier, vol. 167(C), pages 50-62.
    19. Rong, Ke & Kang, Zhengyao & Williamson, Peter J., 2022. "Liability of ecosystem integration and internationalisation of digital firms," Journal of International Management, Elsevier, vol. 28(4).
    20. Baumann, Fabian & Sokolov, Igor M. & Tyloo, Melvyn, 2020. "A Laplacian approach to stubborn agents and their role in opinion formation on influence networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 557(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:spr:comaot:v:27:y:2021:i:2:d:10.1007_s10588-020-09309-6. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.