IDEAS home Printed from https://ideas.repec.org/a/igg/jitwe0/v17y2022i1p1-11.html
   My bibliography  Save this article

Social Network Analysis for Precise Friend Suggestion for Twitter by Associating Multiple Networks Using ML

Author

Listed:
  • Dharmendra Kumar Singh Singh

    (Dr. C. V. Raman University, India)

  • Nithya N.

    (Sona College of Technology, India)

  • Rahunathan L.

    (Kongu Engineering College, India)

  • Preyal Sanghavi

    (R. B. Institute of Management Studies Gujarat Technological University, India)

  • Ravirajsinh Sajubha Vaghela

    (R. B. Institute of Management Studies Gujarat Technological University, India)

  • Poongodi Manoharan

    (Division of Information and Computing Technology, College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar)

  • Mounir Hamdi

    (Division of Information and Computing Technology, College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar)

  • Godwin Brown Tunze

    (Mbeya University of Science and Technology, Tanzania)

Abstract

The main aim in this paper is to create a friend suggestion algorithm that can be used to recommend new friends to a user on Twitter when their existing friends and other details are given. The information gathered to make these predictions includes the user's friends, tags, tweets, language spoken, ID, etc. Based on these features, the authors trained their models using supervised learning methods. The machine learning-based approach used for this purpose is the k-nearest neighbor approach. This approach is by and large used to decrease the dimensionality of the information alongside its feature space. K-nearest neighbor classifier is normally utilized in arrangement-based situations to recognize and distinguish between a few parameters. By using this, the features of the central user's non-friends were compared. The friends and communities of a user are likely to be very different from any other user. Due to this, the authors select a single user and compare the results obtained for that user to suggest friends.

Suggested Citation

  • Dharmendra Kumar Singh Singh & Nithya N. & Rahunathan L. & Preyal Sanghavi & Ravirajsinh Sajubha Vaghela & Poongodi Manoharan & Mounir Hamdi & Godwin Brown Tunze, 2022. "Social Network Analysis for Precise Friend Suggestion for Twitter by Associating Multiple Networks Using ML," International Journal of Information Technology and Web Engineering (IJITWE), IGI Global, vol. 17(1), pages 1-11, January.
    • Handle: RePEc:igg:jitwe0:v:17:y:2022:i:1:p:1-11
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJITWE.304050
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ashwin Muniyappan & Balamuralitharan Sundarappan & Poongodi Manoharan & Mounir Hamdi & Kaamran Raahemifar & Sami Bourouis & Vijayakumar Varadarajan, 2022. "Stability and Numerical Solutions of Second Wave Mathematical Modeling on COVID-19 and Omicron Outbreak Strategy of Pandemic: Analytical and Error Analysis of Approximate Series Solutions by Using HPM," Mathematics, MDPI, vol. 10(3), pages 1-27, January.
    2. M Poongodi & Mohit Malviya & Chahat Kumar & Mounir Hamdi & V Vijayakumar & Jamel Nebhen & Hasan Alyamani, 2022. "New York City taxi trip duration prediction using MLP and XGBoost," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 16-27, March.
    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. Tamil Selvi P. & Kishore Balasubramaniam & Vidhya S. & Jayapandian N. & Ramya K. & Poongodi M. & Mounir Hamdi & Godwin Brown Tunze, 2022. "Social Network User Profiling With Multilayer Semantic Modeling Using Ego Network," International Journal of Information Technology and Web Engineering (IJITWE), IGI Global, vol. 17(1), pages 1-14, January.
    2. Juan Guamán & Karen Portilla & Paúl Arias-Muñoz & Gabriel Jácome & Santiago Cabrera & Luis Álvarez & Bolívar Batallas & Hernán Cadena & Juan Carlos García, 2023. "Multivariate Forecasting Model for COVID-19 Spread Based on Possible Scenarios in Ecuador," Mathematics, MDPI, vol. 11(23), pages 1-13, November.
    3. Rathore, Bhawana & Sengupta, Pooja & Biswas, Baidyanath & Kumar, Ajay, 2024. "Predicting the price of taxicabs using Artificial Intelligence: A hybrid approach based on clustering and ordinal regression models," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 185(C).

    More about this item

    Statistics

    Access and download statistics

    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:igg:jitwe0:v:17:y:2022:i:1:p:1-11. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.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.