TY - GEN
T1 - Extraction of human social behavior from mobile phone sensing
AU - Li, Minshu
AU - Wang, Haipeng
AU - Guo, Bin
AU - Yu, Zhiwen
PY - 2012
Y1 - 2012
N2 - With lots of sensors built in, mobile phones become a pervasive platform for seamlessly sensing of human behaviors. In this paper, we investigate how to use location data and communication records collected from mobile phones to obtain human social interaction features and activity patterns. Social Interaction features refer to the temporal and spatial interactive information, and activity patterns include movement patterns. Meanwhile, the similarities and differences of human behaviors at different ages, as well as distinct occupations are analyzed. The results indicate that different population has a diversity of social interaction and activity patterns, and human social behaviors are highly associated with age and occupation. Furthermore, we make a correlation analysis about social temporal interaction, social spatial interaction and social activity, which lead us to conclude that the three elements are interrelated among young people but not middle-ages. Our work could be a cornerstone for research of personalized psychological health assistance based on mobile phone data.
AB - With lots of sensors built in, mobile phones become a pervasive platform for seamlessly sensing of human behaviors. In this paper, we investigate how to use location data and communication records collected from mobile phones to obtain human social interaction features and activity patterns. Social Interaction features refer to the temporal and spatial interactive information, and activity patterns include movement patterns. Meanwhile, the similarities and differences of human behaviors at different ages, as well as distinct occupations are analyzed. The results indicate that different population has a diversity of social interaction and activity patterns, and human social behaviors are highly associated with age and occupation. Furthermore, we make a correlation analysis about social temporal interaction, social spatial interaction and social activity, which lead us to conclude that the three elements are interrelated among young people but not middle-ages. Our work could be a cornerstone for research of personalized psychological health assistance based on mobile phone data.
KW - health computing
KW - mobile phone data
KW - pervasive computing
KW - Social behavior
UR - http://www.scopus.com/inward/record.url?scp=84870373608&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-35236-2_7
DO - 10.1007/978-3-642-35236-2_7
M3 - 会议稿件
AN - SCOPUS:84870373608
SN - 9783642352355
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 63
EP - 72
BT - Active Media Technology - 8th International Conference, AMT 2012, Proceedings
T2 - 8th International Conference on Active Media Technology, AMT 2012
Y2 - 4 December 2012 through 7 December 2012
ER -