Using decision tree to predict mental health status based on web behavior

It is very important to understand web users´ psychological characteristics, which can help people adapt this rapid and complicated internet world better. Nowadays, web behavior plays a significant role in people´s life and mental health. It is widely accepted in clinical psychology that mental activities and status are expressed in a way of behavior such as preference and choice. Web behavior, as a part of behavior, is supposed to be a meaning to detect users´ mental status. In other words, individuals´ mental status or moods are showed in these details of Internet usage behavior. In this paper, we propose to build a decision tree model to find out the relationship of web users´ mental health and their behavior on the web. Our group conducts a questionnaire test to enroll subjects that use Internet frequently, and then extracts typical behavior features that could be mapped to virtual society and used to predict the users´ mental health. Accordingly, subjects are also required to finish the Psychological Health Inventory (PHI) questionnaire as the criterion variables we are going to predict. Finally we get a collection of behavior features of importance to predict 7 mental disorders and the precision and recall are fairly good.