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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
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    References listed on IDEAS

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    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.
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