Article ID: | iaor20161490 |
Volume: | 32 |
Issue: | 2 |
Start Page Number: | 240 |
End Page Number: | 258 |
Publication Date: | May 2016 |
Journal: | Computational Intelligence |
Authors: | Guo Bin, Liang Yunji, Yu Zhiwen, Li Minshu, Zhou Xingshe |
Keywords: | research, networks, datamining |
The study of geo‐social behaviors has long been a scientific problem. In contrast to traditional social science, which suffers from the problems such as high data collection cost and imported user subjectivity, a new approach is presented to study social behaviors based on mobile phone sensing data. Different from other similar studies on mobile social sensing, three different types of geo‐social behaviors, including online interaction, offline interaction, and mobility patterns, are characterized based on a newly released Nokia mobile phone data set. We further discuss the impact factors to these behaviors as well as the correlation among them. The findings in this article are crucial for many different fields, ranging from urban planning, location‐based services, to social recommendation.