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A personal visual analytics on smartphone usage data
Affiliation:1. School of Information Science and Engineering, Central South University, 410083 Changsha, Hunan, China;2. School of Information Technology and Management, University of Finance and Economics, Changsha 410205, Hunan, China;3. Baidu.Inc, Beijing 100085, China;4. Information Office of ChongQing Technology and Business University, Chongqing 400067,China;1. Missouri University of Science and Technology, Rolla, MO 63128, USA;2. California Polytech State University, San Luis Obispo, CA 93404, USA;1. Politecnico di Torino, Italy;2. Università della Basilicata, Italy;3. Università di Genova, Italy
Abstract: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 personal visual analytic tool is proposed to develop insights and discover knowledge of personal life 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 study, plenty of interesting patterns are discovered by analyzing the data of two smartphone users with different usage styles. We also conduct a one-month user study on several invited volunteers from our laboratory and acquaintance circle to improve our prototype system based on their feedback.
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