Automatic Detection and Prediction of Psychiatric Hospitalizations From Social Media Posts

Zhengping Jiang; Jonathan Zomick; Sarah Ita Levitan; Mark Serper; Julia Hirschberg

Automatic Detection and Prediction of Psychiatric Hospitalizations From Social Media Posts

Zhengping Jiang
, Jonathan Zomick
, Sarah Ita Levitan
, Mark Serper
, Julia Hirschberg

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

We address the problem of predicting psychiatric hospitalizations using linguistic features drawn from social media posts. We formulate this novel task and develop an approach to automatically extract time spans of self-reported psychiatric hospitalizations. Using this dataset, we build predictive models of psychiatric hospitalization, comparing feature sets, user vs. post classification, and comparing model performance using a varying time window of posts. Our best model achieves an F1 of .718 using 7 days of posts. Our results suggest that this is a useful framework for collecting hospitalization data, and that social media data can be leveraged to predict acute psychiatric crises before they occur, potentially saving lives and improving outcomes for individuals with mental illness.

Original language	English
Title of host publication	Computational Linguistics and Clinical Psychology
Subtitle of host publication	Improving Access, CLPsych 2021 - Proceedings of the 7th Workshop, in conjunction with NAACL 2021
Editors	Nazli Goharian, Philip Resnik, Andrew Yates, Molly Ireland, Kate Niederhoffer, Rebecca Resnik
Publisher	Association for Computational Linguistics (ACL)
Pages	116-121
Number of pages	6
ISBN (Electronic)	9781954085411
State	Published - 2021
Externally published	Yes
Event	7th Workshop on Computational Linguistics and Clinical Psychology: Improving Access, CLPsych 2021 - Virtual, Online Duration: 11 Jun 2021 → …

Publication series

Name	Computational Linguistics and Clinical Psychology: Improving Access, CLPsych 2021 - Proceedings of the 7th Workshop, in conjunction with NAACL 2021

Conference

Conference	7th Workshop on Computational Linguistics and Clinical Psychology: Improving Access, CLPsych 2021
City	Virtual, Online
Period	11/06/21 → …

Bibliographical note

Publisher Copyright:
©2021 Association for Computational Linguistics.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Cite this

Jiang, Z., Zomick, J., Levitan, S. I., Serper, M., & Hirschberg, J. (2021). Automatic Detection and Prediction of Psychiatric Hospitalizations From Social Media Posts. In N. Goharian, P. Resnik, A. Yates, M. Ireland, K. Niederhoffer, & R. Resnik (Eds.), Computational Linguistics and Clinical Psychology: Improving Access, CLPsych 2021 - Proceedings of the 7th Workshop, in conjunction with NAACL 2021 (pp. 116-121). (Computational Linguistics and Clinical Psychology: Improving Access, CLPsych 2021 - Proceedings of the 7th Workshop, in conjunction with NAACL 2021). Association for Computational Linguistics (ACL).

Jiang, Zhengping ; Zomick, Jonathan ; Levitan, Sarah Ita et al. / Automatic Detection and Prediction of Psychiatric Hospitalizations From Social Media Posts. Computational Linguistics and Clinical Psychology: Improving Access, CLPsych 2021 - Proceedings of the 7th Workshop, in conjunction with NAACL 2021. editor / Nazli Goharian ; Philip Resnik ; Andrew Yates ; Molly Ireland ; Kate Niederhoffer ; Rebecca Resnik. Association for Computational Linguistics (ACL), 2021. pp. 116-121 (Computational Linguistics and Clinical Psychology: Improving Access, CLPsych 2021 - Proceedings of the 7th Workshop, in conjunction with NAACL 2021).

@inproceedings{465fa2b084bd495f9bb45b53e9046399,

title = "Automatic Detection and Prediction of Psychiatric Hospitalizations From Social Media Posts",

abstract = "We address the problem of predicting psychiatric hospitalizations using linguistic features drawn from social media posts. We formulate this novel task and develop an approach to automatically extract time spans of self-reported psychiatric hospitalizations. Using this dataset, we build predictive models of psychiatric hospitalization, comparing feature sets, user vs. post classification, and comparing model performance using a varying time window of posts. Our best model achieves an F1 of .718 using 7 days of posts. Our results suggest that this is a useful framework for collecting hospitalization data, and that social media data can be leveraged to predict acute psychiatric crises before they occur, potentially saving lives and improving outcomes for individuals with mental illness.",

author = "Zhengping Jiang and Jonathan Zomick and Levitan, \{Sarah Ita\} and Mark Serper and Julia Hirschberg",

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 = "אנגלית",

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 = "116--121",

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 = "ארצות הברית",

}

Jiang, Z, Zomick, J, Levitan, SI, Serper, M & Hirschberg, J 2021, Automatic Detection and Prediction of Psychiatric Hospitalizations From Social Media Posts. in N Goharian, P Resnik, A Yates, M Ireland, K Niederhoffer & R Resnik (eds), Computational Linguistics and Clinical Psychology: Improving Access, CLPsych 2021 - Proceedings of the 7th Workshop, in conjunction with NAACL 2021. Computational Linguistics and Clinical Psychology: Improving Access, CLPsych 2021 - Proceedings of the 7th Workshop, in conjunction with NAACL 2021, Association for Computational Linguistics (ACL), pp. 116-121, 7th Workshop on Computational Linguistics and Clinical Psychology: Improving Access, CLPsych 2021, Virtual, Online, 11/06/21.

Automatic Detection and Prediction of Psychiatric Hospitalizations From Social Media Posts. / Jiang, Zhengping; Zomick, Jonathan; Levitan, Sarah Ita et al.
Computational Linguistics and Clinical Psychology: Improving Access, CLPsych 2021 - Proceedings of the 7th Workshop, in conjunction with NAACL 2021. ed. / Nazli Goharian; Philip Resnik; Andrew Yates; Molly Ireland; Kate Niederhoffer; Rebecca Resnik. Association for Computational Linguistics (ACL), 2021. p. 116-121 (Computational Linguistics and Clinical Psychology: Improving Access, CLPsych 2021 - Proceedings of the 7th Workshop, in conjunction with NAACL 2021).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Hirschberg, Julia

PY - 2021

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AB - We address the problem of predicting psychiatric hospitalizations using linguistic features drawn from social media posts. We formulate this novel task and develop an approach to automatically extract time spans of self-reported psychiatric hospitalizations. Using this dataset, we build predictive models of psychiatric hospitalization, comparing feature sets, user vs. post classification, and comparing model performance using a varying time window of posts. Our best model achieves an F1 of .718 using 7 days of posts. Our results suggest that this is a useful framework for collecting hospitalization data, and that social media data can be leveraged to predict acute psychiatric crises before they occur, potentially saving lives and improving outcomes for individuals with mental illness.

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Jiang Z, Zomick J, Levitan SI, Serper M, Hirschberg J. Automatic Detection and Prediction of Psychiatric Hospitalizations From Social Media Posts. In Goharian N, Resnik P, Yates A, Ireland M, Niederhoffer K, Resnik R, editors, Computational Linguistics and Clinical Psychology: Improving Access, CLPsych 2021 - Proceedings of the 7th Workshop, in conjunction with NAACL 2021. Association for Computational Linguistics (ACL). 2021. p. 116-121. (Computational Linguistics and Clinical Psychology: Improving Access, CLPsych 2021 - Proceedings of the 7th Workshop, in conjunction with NAACL 2021).

Automatic Detection and Prediction of Psychiatric Hospitalizations From Social Media Posts

Abstract

Publication series

Conference

Bibliographical note

UN SDGs

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