Predictability of evolving contacts and triadic closure in human face-to-face proximity networks

  • Christoph Scholz
  • Martin Atzmueller
  • Mark Kibanov
  • Gerd Stumme
Original Article


The analysis of link structures and particularly their dynamics is important for enhancing our understanding of the underlying (social) processes. This paper analyzes such structures in networks of face-to-face spatial proximity: we focus on evolving contacts and triadic closure and present new insights on the dynamic and static contact behavior in real-world networks, where we utilize face-to-face contact networks collected at three different conferences using the social conference guidance system Conferator [Atzmueller et al. 2011, 2014]. We analyze network dynamics and the predictability of all, new and recurring links. Furthermore, we especially investigate the strength of ties, their connection to triadic closure, and examine influence factors for predicting triadic closure in face-to-face proximity networks.


Link Prediction Common Neighbor Contact Network Contact Duration Predictor Score 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work has been supported by the VENUS research cluster at the interdisciplinary Research Center for Information System Design (ITeG) at Kassel University. We thank the SocioPatterns collaboration for providing privileged access to the SocioPatterns sensing platform that was used in collecting the contact data.


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Copyright information

© Springer-Verlag Wien 2014

Authors and Affiliations

  • Christoph Scholz
    • 1
  • Martin Atzmueller
    • 1
  • Mark Kibanov
    • 1
  • Gerd Stumme
    • 1
  1. 1.Knowledge and Data Engineering GroupUniversity of KasselKasselGermany

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