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

Jina Kim · Jieon Lee · Eunil Park · Jinyoung Han

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Mental Health via Writing Sentiment Analysis and Opinion Mining Emotion and Mood Recognition

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.

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References

2009Is There Social Capital in a Social Network Site?: Facebook Use and College Students' Life Satisfaction, Trust, and Participation 2009Mental Health Problems and Help-Seeking Behavior Among College Students 2021Predicting Depression via Social Media 2005Failure and Delay in Initial Treatment Contact After First Onset of Mental Disorders in the National Comorbidity Survey Replication 2017Instagram photos reveal predictive markers of depression

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2022RETRACTED: Deep Learning for Depression Detection from Textual Data 2021A textual-based featuring approach for depression detection using machine learning classifiers and social media texts 2022Explainable depression detection with multi-aspect features using a hybrid deep learning model on social media 2022Depression Detection from Social Media Text Analysis using Natural Language Processing Techniques and Hybrid Deep Learning Model 2021Machine Learning for Mental Health in Social Media: Bibliometric Study 2021Automatic detection of depression symptoms in twitter using multimodal analysis 2022A Novel Text Mining Approach for Mental Health Prediction Using Bi-LSTM and BERT Model

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