Visualizing Users’ Characteristics Based On Mobile Device Log Data

With the dramatic development of mobile internet in our country, the amount of mobile users is growing rapidly and many kinds of mobile applications are popping up. It is a very meaningful thing that we abstract valuable information from mobile device log data and report the analysis result through visualization method to help application developers and distributors maximize monetization opportunity. Currently, most of mobile log data analysis work is about single dimension statistics result, like app download rank. In this paper, we will mine deep information hiding behind mobile device log data and summarize users’ characteristics. We propose a novel method for analyzing users’ characteristics and computing users’portrait. We abstract an app topic model based on mobile log data, and build user clusters according to app topics, and design two visualization methods to show users’characteristics clusters. In addition, we combine user clusters with time information and geographical information, to show users’ characteristics from more dimensions. Finally, according to the research, we implement a mobile log data visualization analysis B/S system, and demonstrate the validity of the method by case study.