IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v618y2023ics0378437123002650.html
   My bibliography  Save this article

ASN: A method of optimality for seed identification in the influence diffusion process

Author

Listed:
  • Devi, Kalyanee
  • Tripathi, Rohit

Abstract

The influence phenomenon in any social network highly relies on its influential seed nodes. However, the majority of the existing research is on single-phase diffusion models where the seed nodes are chosen at once to initiate the diffusion process, and the influence diffusion is primarily investigated using progressive models. Thus, these models may not work effectively for some real-life events where the influenced users get uninfluenced in the future. Also, many existing seed selection schemes either rely on the network’s structure or relationships between nodes. Hence, these methods might not offer an optimal seed identification solution. This paper presents a non-progressive diffusion model named the ICIS model, which handles non-progressive influence diffusion across multiple time phases. This paper establishes a relation between the node’s state change in the ICIS model and the dynamics of queueing theory to analyse the influence potential of the nodes. In this paper, we also propose an optimal seed selection method named the ‘ASN’ method that considers the effects of a node’s state change to accurately compute the advantage value for each node. Thus, regardless of the topological characteristics of the network, this method offers an optimal means of choosing the seed nodes in the network. An experimental investigation on a few networks illustrates the efficiency of the proposed method. By utilizing the ASN method, we also estimate the percentage deviation of many existing seed selection techniques from the optimal solution.

Suggested Citation

  • Devi, Kalyanee & Tripathi, Rohit, 2023. "ASN: A method of optimality for seed identification in the influence diffusion process," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 618(C).
    • Handle: RePEc:eee:phsmap:v:618:y:2023:i:c:s0378437123002650
    DOI: 10.1016/j.physa.2023.128710
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437123002650
    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.2023.128710?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. Zhan, Xiu-Xiu & Liu, Chuang & Zhou, Ge & Zhang, Zi-Ke & Sun, Gui-Quan & Zhu, Jonathan J.H. & Jin, Zhen, 2018. "Coupling dynamics of epidemic spreading and information diffusion on complex networks," Applied Mathematics and Computation, Elsevier, vol. 332(C), pages 437-448.
    2. Ma, Qian & Ma, Jun, 2017. "Identifying and ranking influential spreaders in complex networks with consideration of spreading probability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 312-330.
    3. Rohit Tripathi & Gautam Barua, 2016. "Dynamic internet pricing with service level agreements for multihomed clients," Netnomics, Springer, vol. 17(2), pages 121-156, September.
    4. Ling Zhang & Manman Luo & Robert J. Boncella, 2020. "Product information diffusion in a social network," Electronic Commerce Research, Springer, vol. 20(1), pages 3-19, March.
    5. Bhattacharya, Saumik & Gaurav, Kumar & Ghosh, Sayantari, 2019. "Viral marketing on social networks: An epidemiological perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 478-490.
    6. Ellis, Craig A. & Parbery, Simon A., 2005. "Is smarter better? A comparison of adaptive, and simple moving average trading strategies," Research in International Business and Finance, Elsevier, vol. 19(3), pages 399-411, September.
    7. Salavati, Chiman & Abdollahpouri, Alireza & Manbari, Zhaleh, 2018. "BridgeRank: A novel fast centrality measure based on local structure of the network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 635-653.
    8. Singh, Shashank Sheshar & Kumar, Ajay & Singh, Kuldeep & Biswas, Bhaskar, 2019. "C2IM: Community based context-aware influence maximization in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 796-818.
    9. Stephen P. Borgatti, 2006. "Identifying sets of key players in a social network," Computational and Mathematical Organization Theory, Springer, vol. 12(1), pages 21-34, 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. Huang, He & Chen, Yahong & Ma, Yefeng, 2021. "Modeling the competitive diffusions of rumor and knowledge and the impacts on epidemic spreading," Applied Mathematics and Computation, Elsevier, vol. 388(C).
    2. Mark J. O. Bagley, 2019. "Networks, geography and the survival of the firm," Journal of Evolutionary Economics, Springer, vol. 29(4), pages 1173-1209, September.
    3. Liu, Weiwei & Song, Yifan & Bi, Kexin, 2021. "Exploring the patent collaboration network of China's wind energy industry: A study based on patent data from CNIPA," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    4. 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).
    5. Karasu, Seçkin & Altan, Aytaç, 2022. "Crude oil time series prediction model based on LSTM network with chaotic Henry gas solubility optimization," Energy, Elsevier, vol. 242(C).
    6. Hosseinali Salemi & Austin Buchanan, 2022. "Solving the Distance-Based Critical Node Problem," INFORMS Journal on Computing, INFORMS, vol. 34(3), pages 1309-1326, May.
    7. Capponi, Agostino & Corell, Felix & Stiglitz, Joseph E., 2022. "Optimal bailouts and the doom loop with a financial network," Journal of Monetary Economics, Elsevier, vol. 128(C), pages 35-50.
    8. Yuan, Guanghui & Han, Jingti & Zhou, Lei & Liang, Hejun & Zhang, Yicheng, 2019. "Supply and demand law under variable information," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    9. Xinyu Huang & Dongming Chen & Dongqi Wang & Tao Ren, 2020. "MINE: Identifying Top- k Vital Nodes in Complex Networks via Maximum Influential Neighbors Expansion," Mathematics, MDPI, vol. 8(9), pages 1-25, August.
    10. Zhao, Shuying & Sun, Shaowei, 2023. "Identification of node centrality based on Laplacian energy of networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    11. Xuzhen Zhu & Jinming Ma & Xin Su & Hui Tian & Wei Wang & Shimin Cai, 2019. "Information Spreading on Weighted Multiplex Social Network," Complexity, Hindawi, vol. 2019, pages 1-15, November.
    12. Raddant, Matthias & Takahashi, Hiroshi, 2019. "The Japanese corporate board network," Kiel Working Papers 2130, Kiel Institute for the World Economy (IfW Kiel).
    13. Liberati, Caterina & Marzo, Massimiliano & Zagaglia, Paolo & Zappa, Paola, 2012. "Structural distortions in the Euro interbank market: the role of 'key players' during the recent market turmoil," MPRA Paper 40223, University Library of Munich, Germany.
    14. Michel Grabisch & Agnieszka Rusinowska, 2015. "Lattices in Social Networks with Influence," International Game Theory Review (IGTR), World Scientific Publishing Co. Pte. Ltd., vol. 17(01), pages 1-18.
    15. Andrea Galeotti & Benjamin Golub & Sanjeev Goyal, 2020. "Targeting Interventions in Networks," Econometrica, Econometric Society, vol. 88(6), pages 2445-2471, November.
    16. Marco Di Summa & Syed Md Omar Faruk, 2023. "Critical node/edge detection problems on trees," 4OR, Springer, vol. 21(3), pages 439-455, September.
    17. Venel, Xavier, 2021. "Regularity of dynamic opinion games," Games and Economic Behavior, Elsevier, vol. 126(C), pages 305-334.
    18. Gallo, Julie Le & Plunket, Anne, 2020. "Regional gatekeepers, inventor networks and inventive performance: Spatial and organizational channels," Research Policy, Elsevier, vol. 49(5).
    19. Yadira Méndez-Lemus & Antonio Vieyra & Lorena Poncela, 2017. "Peri-urban local governance? Intra-government relationships and social capital in a peripheral municipality of Michoacán, Mexico," Progress in Development Studies, , vol. 17(1), pages 1-23, January.
    20. Rafiee, Samira & Salavati, Chiman & Abdollahpouri, Alireza, 2020. "CNDP: Link prediction based on common neighbors degree penalization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(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:618:y:2023:i:c:s0378437123002650. 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.