top of page

Subscribe to get the latest updates from Receptiviti

Predicting Psychiatric Hospitalizations using Social Media Posts

The researchers address the challenge of predicting psychiatric hospitalizations through social media posts. They propose a framework that extracts time spans of self-reported psychiatric hospitalizations from social media data to build predictive models of psychiatric hospitalization. The study compares various feature sets and classification methods to obtain the best predictive model. The results show that social media data can be leveraged to predict acute psychiatric crises before they occur, with the best model achieving an F1 of .718 using 7 days of posts. This framework is crucial in collecting hospitalization data and can potentially save lives and improve outcomes for individuals with mental illness.

Read the research: Automatic Detection and Prediction of Psychiatric Hospitalizations From Social Media Posts

Subscribe to the blog and get notified of new content:

Customer Stories

Customer Stories and Use Cases

Organizations of all sizes have integrated Receptiviti into their technologies and processes to uncover critical insights about the people who matter to their businesses.