A deep learning model for detecting mental illness from user content on social media

TLDR

Social media users frequently share feelings or emotional states in their posts. The study aims to develop a deep learning model that identifies users’ mental states from their posts, to help detect potential mental illness and serve as a supplementary monitoring tool. The authors trained a deep learning model on posts from Reddit mental health communities to classify users’ mental states. The model accurately classified posts into six mental disorders, including depression, anxiety, bipolar, borderline personality disorder, schizophrenia, and autism.

Abstract

Abstract Users of social media often share their feelings or emotional states through their posts. In this study, we developed a deep learning model to identify a user’s mental state based on his/her posting information. To this end, we collected posts from mental health communities in Reddit . By analyzing and learning posting information written by users, our proposed model could accurately identify whether a user’s post belongs to a specific mental disorder, including depression, anxiety, bipolar, borderline personality disorder, schizophrenia, and autism. We believe our model can help identify potential sufferers with mental illness based on their posts. This study further discusses the implication of our proposed model, which can serve as a supplementary tool for monitoring mental health states of individuals who frequently use social media.