Cross-Platform Detection of Psychiatric Hospitalization via Social Media Data: Comparison Study.

ABSTRACT:

Background

Previous research has shown the feasibility of using machine learning models trained on social media data from a single platform (eg, Facebook or Twitter) to distinguish individuals either with a diagnosis of mental illness or experiencing an adverse outcome from healthy controls. However, the performance of such models on data from novel social media platforms unseen in the training data (eg, Instagram and TikTok) has not been investigated in previous literature.

Objective

Our study examined the feasibility of building machine learning classifiers that can effectively predict an upcoming psychiatric hospitalization given social media data from platforms unseen in the classifiers' training data despite the preliminary evidence on identity fragmentation on the inve

SUBMITTER: Nguyen VC 

PROVIDER: S-EPMC9840099 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature