Discovering Links among Social Networks

  • Francesco Buccafurri
  • Gianluca Lax
  • Antonino Nocera
  • Domenico Ursino
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7524)

Abstract

Distinct social networks are interconnected via bridge users, who play thus a key role when crossing information is investigated in the context of Social Internetworking analysis. Unfortunately, not always users make their role of bridge explicit by specifying the so-called me edge (i.e., the edge connecting the accounts of the same user in two distinct social networks), missing thus a potentially very useful information. As a consequence, discovering missing me edges is an important problem to face in this context yet not so far investigated. In this paper, we propose a common-neighbors approach to detecting missing me edges, which returns good results in real life settings. Indeed, an experimental campaign shows both that the state-of-the-art common-neighbors approaches cannot be effectively applied to our problem and, conversely, that our approach returns precise and complete results.

Keywords

Link Prediction Link Mining Social networks Social Internetworking 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Francesco Buccafurri
    • 1
  • Gianluca Lax
    • 1
  • Antonino Nocera
    • 1
  • Domenico Ursino
    • 1
  1. 1.DIMETUniversity “Mediterranea” of Reggio CalabriaReggio CalabriaItaly

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