A visual analytics approach for exploring individual behaviors in smartphone usage data

The percentage of individuals frequently using their smartphones in work and life is increasing steadily. The interactions between individuals and their smartphones can produce large amounts of usage data, which contain rich information about smartphone owners usage habits and their daily life. In this paper, a visual analytic tool is proposed to discover and understand individual behavior patterns in smartphone usage data. Four cooperated visualization views and many interactions are provided in this tool to visually explore the temporal features of various interactive events between smartphones and their users, the hierarchical associations among event types, and the detailed distributions of massive event sequences. In the case studies, plenty of interesting patterns are discovered by analyzing the data of two smartphone users with different usage styles.