@inproceedings{597cc98cbdc44fafb7727f860e10a93d,
title = "On the State of Social Media Data for Mental Health Research",
abstract = "Data-driven methods for mental health treatment and surveillance have become a major focus in computational science research in the last decade. However, progress in the domain remains bounded by the availability of adequate data. Prior systematic reviews have not necessarily made it possible to measure the degree to which data-related challenges have affected research progress. In this paper, we offer an analysis specifically on the state of social media data that exists for conducting mental health research. We do so by introducing an open-source directory of mental health datasets, annotated using a standardized schema to facilitate meta-analysis.1",
author = "Keith Harrigian and Carlos Aguirre and Mark Dredze",
note = "Publisher Copyright: {\textcopyright}2021 Association for Computational Linguistics.; 7th Workshop on Computational Linguistics and Clinical Psychology: Improving Access, CLPsych 2021 ; Conference date: 11-06-2021",
year = "2021",
language = "English (US)",
series = "Computational Linguistics and Clinical Psychology: Improving Access, CLPsych 2021 - Proceedings of the 7th Workshop, in conjunction with NAACL 2021",
publisher = "Association for Computational Linguistics (ACL)",
pages = "15--24",
editor = "Nazli Goharian and Philip Resnik and Andrew Yates and Molly Ireland and Kate Niederhoffer and Rebecca Resnik",
booktitle = "Computational Linguistics and Clinical Psychology",
address = "United States",
}