AAAI Publications, Seventh International AAAI Conference on Weblogs and Social Media

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New Insights and Methods For Predicting Face-To-Face Contacts
Christoph Scholz, Martin Atzmueller, Alain Barrat, Ciro Cattuto, Gerd Stumme

Last modified: 2013-06-28


The prediction of new links in social networks is a challeng- ing task. In this paper, we focus on predicting links in net- works 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 pre- diction task: We introduce an unsupervised link prediction method based on rooted random walks, and show that it out- performs state-of-the-art unsupervised link prediction meth- ods. 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.


Link Prediction, RFID, Social Network Analysis

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