A Deep Learning Framework Using App Usage Record to Predict Demographic Information

In the mobile Internet era, demographic information plays an important role in many personalized services and research areas such as content recommendation [1], advertising [2], and behavioral prediction [3]. However, this information is treated as private data and is difficult to access. Therefore, the prediction of demographic information has aroused research interest. There are already some studies that predict demographic information based on user-generated content [4], smartphone sensor data, and user biometric data [5]. In this paper, we introduce a new method that uses App usage record data to predict the demographic information of smartphone users. App usage record data is a set of easily accessible, rich and insightful data. We propose a deep learning framework that uses a convolutional neural network(CNN) to predict the demographic information of smartphone users through app usage record data. We use a set of data with 6-months App usage record of about 5,000 users to train our prediction model. The CNN model we proposed has achieved good prediction performance on the training data set. In the comparative experiment, the prediction effect of our model is also better than the effect of the three classical machine learning algorithms.