Ontology highlight
ABSTRACT: Background
Antidepressants are known to show heterogeneous effects across individuals and conditions, posing challenges to understanding their efficacy in mental health treatment. Social media platforms enable individuals to share their day-to-day concerns with others and thereby can function as unobtrusive, large-scale, and naturalistic data sources to study the longitudinal behavior of individuals taking antidepressants.Objective
We aim to understand the side effects of antidepressants from naturalistic expressions of individuals on social media.Methods
On a large-scale Twitter data set of individuals who self-reported using antidepressants, a quasi-experimental study using unsupervised language analysis was conducted to extract keywords that distinguish individua
SUBMITTER: Saha K
PROVIDER: S-EPMC8077932 | biostudies-literature | 2021 Mar
REPOSITORIES: biostudies-literature