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An approach for predicting missing links in social network using node attribute and path information

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Abstract

In social networks, link prediction is the task to identify links in future. Many existing link prediction techniques used similarity scores to predict links. An essential concern in the link prediction problem is identifying missing links between the nodes when there are no common neighbors between the nodes. Considering this, a new algorithm proposed, namely Similarity-based Algorithm using Degree and Common Neighbour (SADCN) which includes a node's degree in the shortest path and common neighbor. For experiment evaluation, three datasets are used to test our method performance against some standard similarity index and the recently proposed algorithms for link prediction, which depicts that our approach achieved comparable AUC values to those that consider common neighbors and it gives better AUC for those links, where no mutual neighbour between the two nodes exists. Finally, we create feature vectors and use XGB classifiers for predicting links. It shows that our proposed algorithm can improve the F-measure and accuracy in a feature based link prediction model.

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Funding

No external funding is done for this reasearch work. The dataset used here is available online.

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Authors and Affiliations

  1. University School of Information, Communication and Technology, Guru Gobind Singh Indraprastha University, New Delhi, India

    Ankita Singh

  2. Indira Gandhi Delhi Technical University for Women, Delhi, India

    Ankita Singh

  3. NSUT East Campus (Formerly AIACTR), Delhi, India

    Nanhay Singh

Authors
  1. Ankita Singh
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  2. Nanhay Singh
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Correspondence to Ankita Singh.

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Human and animals rights

In Social network users make relationships and express their thoughts to each other. Link prediction is one of the main research areas where links/relationship between users can be predicted which may further apply in different fields like recommendation systems, coauthorship networks etc. This research involves finding missing links between users of any social network. For this we have used three dataset which is publicly available: Karat club dataset, dolphin dataset and Polbook dataset. There is no biological material used in the research paper.

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Not Applicable as no such study has been done, the dataset used for implementation is publicly available (online). Related reference to the same has been added in the research paper.

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Singh, A., Singh, N. An approach for predicting missing links in social network using node attribute and path information. Int J Syst Assur Eng Manag 13, 944–956 (2022). https://doi.org/10.1007/s13198-021-01371-w

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