@inproceedings{9c7122a3c4cb4bf3aa5e44c2b0463d8e,
title = "Reality mining: Digging the impact of friendship and location on crowd behavior",
abstract = "Crowd behavior of human deserves to be studied since it is common that people are influenced and change their behavior when being in a group. In pervasive computing research, an amount of work has been directed towards discovering human movement patterns based on wireless networks, mainly focusing on movements of individuals. It is surprising that social interaction among individuals in a crowd is largely neglected. Mobile phones offer on-body tracking and they are already deployed on a large scale, allowing the characterization of user behav- ior through large amounts of wireless information collected by mobile phones. In this paper, we observe and analyze the impact of friendship and location attributes on crowd behavior, using location-based wire- less mobility information. This is a cornerstone for predicting crowd behavior, which can be used in a large number of applications such as crowdsourcing-based technology, traffic management, crowd safety, and infrastructure deployment.",
keywords = "Complex social networks, Crowd behavior, Mobile devices, Wearable computing",
author = "Yuanfang Chen and Ortiz, \{Antonio M.\} and Noel Crespi and Lei Shu and Lin Lv",
note = "Publisher Copyright: {\textcopyright} Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2014.; 10th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, MOBIQUITOUS 2013 ; Conference date: 02-12-2013 Through 04-12-2013",
year = "2014",
month = jan,
day = "1",
doi = "10.1007/978-3-319-11569-6\_12",
language = "English",
series = "Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST",
publisher = "Springer Verlag",
pages = "142--154",
editor = "Ivan Stojmenovic and Zixue Cheng and Song Guo",
booktitle = "Mobile and Ubiquitous Systems",
}