Extraction of Human Social Behavior from Mobile Phone Sensing

Abstract

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.KeywordsSocial behaviormobile phone datapervasive computinghealth computing