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Large-Scale Parallel Matching of Social Network Profiles

  • Alexander PanchenkoEmail author
  • Dmitry Babaev
  • Sergei Obiedkov
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 542)

Abstract

A profile matching algorithm takes as input a user profile of one social network and returns, if existing, the profile of the same person in another social network. Such methods have immediate applications in Internet marketing, search, security, and a number of other domains, which is why this topic saw a recent surge in popularity.

In this paper, we present a user identity resolution approach that uses minimal supervision and achieves a precision of 0.98 at a recall of 0.54. Furthermore, the method is computationally efficient and easily parallelizable. We show that the method can be used to match Facebook, the most popular social network globally, with VKontakte, the most popular social network among Russian-speaking users.

Keywords

User identify resolution Entity resolution Profile matching Record linkage Social networks Social network analysis Facebook Vkontakte 

Notes

Acknowledgements

This research was conducted as part of a project funded by Digital Society Laboratory LLC. We thank Prof. Chris Biemann and three anonymous reviewers for their thorough comments that significantly improved quality of this paper.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Alexander Panchenko
    • 1
    Email author
  • Dmitry Babaev
    • 2
  • Sergei Obiedkov
    • 3
  1. 1.FG Language TechnologyTU DarmstadtDarmstadtGermany
  2. 2.Tinkoff Credit Systems Inc.MoscowRussia
  3. 3.National Research University Higher School of EconomicsMoscowRussia

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