New Insights and Methods for Predicting Face-To-Face Contacts

Christoph Scholz, Martin Atzmueller, Gerd Stumme, Alain Barrat, Ciro Cattuto Proceedings of the 7th International Conference on Weblogs and Social Media (ICWSM-13), July 2013, Boston, USA

The prediction of new links in social networks is a challenging task. In this paper, we focus on predicting links in networks of face-to-face spatial proximity by using information from online social networks, such as co-authorship networks in DBLP, and a number of node level attributes.

First, we analyze influence factors for the link prediction task. Then, we propose a novel method that combines information from different networks and node level attributes for the prediction task: We introduce an unsupervised link prediction method based on rooted random walks, and show that it outperforms state-of-the-art unsupervised link prediction methods. We present an evaluation using three real-world datasets.Furthermore, we discuss the impact of our results and of the insights we glean in the field of link prediction and human contact behavior.


URL: http://www.icwsm.org/2013/program/program/

PDF: http://www.cpt.univ-mrs.fr/~barrat/icwsm13.pdf

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