Abstract. In their daily activities, users interact multiple times with mobile applications. This generates huge amounts of data related to these interactions that, when filtered and analyzed, would give insights on the behavior of the users while using an application. In this paper, we consider a real-world mobile digital publishing platform, named Viewerplus, which enables a digital, augmented fruition of content from traditional magazines. The objective is to develop a tool that allows the human editors to analyze the reading behavior of the users, by providing analytics that show how the users read magazine issues (i.e., how they browse an issue and move inside the app, which portions of an issue are most frequently read and which frequency, and which topics are of interest for the users during a reading session). The tool has been developed by employing a dataset extracted from the reading sessions of a magazine of an important international publisher. In this work we also employ the dataset to present a preliminary study of the user reading behavior
