Link Prediction in Social Networking using Machine Learning


  • Lakshitaa Sehgal
  • Sannidhi Sri Sai Hanuma
  • Paruchuri Ratan Chowdary
  • Aaditya Singh
  • Vishwas Gowdihalli Mahalingappa
  • Manikanta Ranganath


link prediction, social networking


Social Networks specifical consciousness on building on social relations among customers who share common pastimes, background, real-lifestyles connections, and so on. People may additionally not need to maximize their social influence. For example, business page owners on Instagram want to influence as many human beings as viable for or their business benefits. However, the network is evolving in time, new customers are joining, adding pals, new connections between antique users, and so forth. Based on the contemporary community we need so one can expect the upcoming adjustments in the network and make tips accordingly. We have a photograph of Facebook’s social network at the time (say ‘t’) and based on it, we want to expect the destiny possible links. In this paper, we can be sharing our technique using machine learning to solve this example observe.


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How to Cite

L. Sehgal, S. S. S. Hanuma, P. R. Chowdary, A. Singh, V. G. Mahalingappa, and M. Ranganath, “Link Prediction in Social Networking using Machine Learning”, IJRESM, vol. 5, no. 2, pp. 44–48, Feb. 2022.




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