IEEE International Conference on Privacy, Security, Risk and Trust, стр. 312--321. Washington, DC, USA, IEEE Computer Society, (2012)

While the analysis of online social networks is a prominent research topic, offline real-world networks are still not covered extensively. However, their analysis can provide important insights into human behavior. In this paper, we analyze influence factors for link prediction in human contact networks. Specifically, we consider the prediction of new links, and extend it to the analysis of recurring links. Furthermore, we consider the impact of stronger ties for the prediction. The results and insights of the analysis are a first step onto predictability applications for human contact networks.

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http://dx.doi.org/10.1109/SocialCom-PASSAT.2012.49

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@inproceedings{Scholz:2012:PHC:2411131.2411662,
  abstract = {While the analysis of online social networks is a prominent research topic, offline real-world networks are still not covered extensively. However, their analysis can provide important insights into human behavior. In this paper, we analyze influence factors for link prediction in human contact networks. Specifically, we consider the prediction of new links, and extend it to the analysis of recurring links. Furthermore, we consider the impact of stronger ties for the prediction. The results and insights of the analysis are a first step onto predictability applications for human contact networks.},
  acmid = {2411662},
  added-at = {2013-05-28T11:47:43.000+0200},
  address = {Washington, DC, USA},
  author = {Scholz, Christoph and Atzmueller, Martin and Stumme, Gerd},
  biburl = {https://puma.uni-kassel.de/bibtex/2b8771cc1fc02b5bb679c4a293eae517d/stumme},
  booktitle = {Proceedings of the 2012 ASE/IEEE International Conference on Social Computing and 2012 ASE/IEEE International Conference on Privacy, Security, Risk and Trust},
  description = {On the Predictability of Human Contacts},
  doi = {10.1109/SocialCom-PASSAT.2012.49},
  interhash = {9bc5d42018dbe8b926be214190258b3c},
  intrahash = {b8771cc1fc02b5bb679c4a293eae517d},
  isbn = {978-0-7695-4848-7},
  keywords = {2012 contacts factors human influence itegpub l3s myown predictability venus},
  numpages = {10},
  pages = {312--321},
  publisher = {IEEE Computer Society},
  series = {SOCIALCOM-PASSAT '12},
  timestamp = {2013-05-28T11:47:43.000+0200},
  title = {On the Predictability of Human Contacts: Influence Factors and the Strength of Stronger Ties},
  url = {http://dx.doi.org/10.1109/SocialCom-PASSAT.2012.49},
  year = 2012
}

%0 Conference Paper
%1 Scholz:2012:PHC:2411131.2411662
%A Scholz, Christoph
%A Atzmueller, Martin
%A Stumme, Gerd
%B Proceedings of the 2012 ASE/IEEE International Conference on Social Computing and 2012 ASE/IEEE International Conference on Privacy, Security, Risk and Trust
%C Washington, DC, USA
%D 2012
%I IEEE Computer Society
%K 2012 contacts factors human influence itegpub l3s myown predictability venus
%P 312--321
%R 10.1109/SocialCom-PASSAT.2012.49
%T On the Predictability of Human Contacts: Influence Factors and the Strength of Stronger Ties
%U http://dx.doi.org/10.1109/SocialCom-PASSAT.2012.49
%X While the analysis of online social networks is a prominent research topic, offline real-world networks are still not covered extensively. However, their analysis can provide important insights into human behavior. In this paper, we analyze influence factors for link prediction in human contact networks. Specifically, we consider the prediction of new links, and extend it to the analysis of recurring links. Furthermore, we consider the impact of stronger ties for the prediction. The results and insights of the analysis are a first step onto predictability applications for human contact networks.
%@ 978-0-7695-4848-7

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