Predicting Future Mental Illness from Social Media: a Big Data Approach

Author:

Thorstad Robert,Wolff Phillip

Abstract

The current research investigates whether people’s everyday language contains sufficient signal to predict the future occurrence of mental illness. Language samples were collected from the social media website Reddit drawing on posts to discussion groups focusing on different kinds of mental illness (clinical subreddits), as well as to discussion groups focusing on non-mental health topics (non-clinical subreddits). As expected, words drawn from clinical subreddits could be used to distinguish several kinds of mental illness (ADHD, Anxiety, Bipolar, Depression). Interestingly, words drawn from non-clinical subreddits (e.g., travel, cooking, cars) could also be used to distinguish different categories of mental illness, implying that the impact of mental illness spills over to into topics unrelated to mental illness. Most importantly, words derived from nonclinical subreddits predicted future postings to clinical subreddits, implying that everyday language contains signal about the likelihood of future mental illness, possibly before people are aware of their mental health condition. Finally, while models trained on clinical subreddits learned to focus on words indicating disorder-specific symptoms, models trained to predict future mental illness learned to focus on words indicating life stress, providing insight into the time-course of developing a mental illness.

Publisher

Center for Open Science

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Sentiment Analysis on Depression Detection: A Review;Lecture Notes in Networks and Systems;2022

2. Classification of mental illness from user content on social media;INTERNATIONAL SCIENTIFIC AND PRACTICAL CONFERENCE “TECHNOLOGY IN AGRICULTURE, ENERGY AND ECOLOGY” (TAEE2022);2022

3. Big data analytics meets social media: A systematic review of techniques, open issues, and future directions;Telematics and Informatics;2021-03

4. Therapy Recommendation Based on Level of Depression Using Social Media Data;Data Science and Security;2020-08-01

5. A Systematic Review of Smart Mental Healthcare;SSRN Electronic Journal;2019

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