Network Traffic and User Behavior Analysis of Mobile Reading Applications

Mobile reading ranks No.4 on the permeate proportion of the mobile Internet applications and is increasing gradually. Understanding user behaviors of mobile reading is important for service provider. However, few work has been done on reading analysis. In this paper, we provide an approach to solve this problem based on cloud computing platform including HDFS and Apache Pig. Our study is carried out based on the data collected from the ISP network which covered an entire city in southern China. We presented the feature of traffic and behavior in three aspects. First, we compared the service condition of several popular websites in mobile reading field and found the basic law that traffic distribution tits. Second, we recognize user sessions via time threshold method and found some interesting phenomenon about session duration. Finally, we break user actions down into discrete categories and summarized the characteristics of each reading application. We compared user acceptance of different applications from three perspectives, which are user loyalty, user behavior and cross-user distribution respectively.