Analysis reddit data for the prediction and detection of depression

Abstract

The digital presence of a person is defined by his/her digital footprint. A major contributor to the digital footprint is the user’s activity on Social Media. On such sites, the user expresses himself on what s/he thinks, what s/he likes and what s/he feels. Based on this information, we can predict and determine the psychological wellbeing of the user. The aim of this study is to use the Reddit posts and comments of various Reddit users to determine which are the best models to use when detecting or predicting depressive disorders in users. In this study, four different classifiers were implemented, and their results were compared in order to determine which is the best performing model out of the four classifiers. The implemented classifiers are a Logistic Regression model, a Random Forest Classifier, a Support Vector Machine classifier, and a Convolutional Neural Network model. After evaluating the implemented models, it was found that the Random Forest and the Support Vector Machine were the best models at detecting whether a user had depression or not. Moreover, after a qualitative evaluation of the models’ results, it was found that the implemented models are capable of detecting possible depression in users who have not yet been clinically diagnosed with the psychological disorder.