Knowledge and Information Systems

, Volume 55, Issue 1, pp 1–13 | Cite as

Exploiting reciprocity toward link prediction

  • Niladri SettEmail author
  • Devesh
  • Sanasam Ranbir Singh
  • Sukumar Nandi
Regular Paper


This paper addresses link prediction problem in directed networks by exploiting reciprocative nature of human relationships. It first proposes a null model to present evidence that reciprocal links influence the process of “triad formation”. Motivated by this, reciprocal links are exploited to enhance link prediction performance in three ways: (a) a reciprocity-aware link weighting technique is proposed, and existing weighted link prediction methods are applied over the resultant weighted network; (b) new link prediction methods are proposed, which exploit reciprocity; and (c) existing and proposed methods are combined toward supervised prediction to enhance the prediction performance further. All experiments are carried out on two real directed network datasets.


Link prediction Reciprocity Link strength 


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Copyright information

© Springer-Verlag London 2017

Authors and Affiliations

  • Niladri Sett
    • 1
    Email author
  • Devesh
    • 1
    • 2
  • Sanasam Ranbir Singh
    • 1
  • Sukumar Nandi
    • 1
  1. 1.Department of Computer Science and EngineeringIndian Institute of Technology GuwahatiGuwahatiIndia
  2. 2.Paytm, BPL Software CenterBengaluruIndia

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