Home > Research > Publications & Outputs > A computational linguistic study of personal re...

Research

Links

Text available via DOI:

View graph of relations

A computational linguistic study of personal recovery in bipolar disorder

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Published

Standard

A computational linguistic study of personal recovery in bipolar disorder. / Jagfeld, Glorianna.
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop. Association for Computational Linguistics, 2019. P19-2003.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

Jagfeld, G 2019, A computational linguistic study of personal recovery in bipolar disorder. in Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop., P19-2003, Association for Computational Linguistics, ACL Student Research Workshop (SRW), Florence, Italy, 28/07/19. https://doi.org/10.18653/v1/P19-2003

APA

Jagfeld, G. (2019). A computational linguistic study of personal recovery in bipolar disorder. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop Article P19-2003 Association for Computational Linguistics. https://doi.org/10.18653/v1/P19-2003

Vancouver

Jagfeld G. A computational linguistic study of personal recovery in bipolar disorder. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop. Association for Computational Linguistics. 2019. P19-2003 doi: 10.18653/v1/P19-2003

Author

Jagfeld, Glorianna. / A computational linguistic study of personal recovery in bipolar disorder. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop. Association for Computational Linguistics, 2019.

Bibtex

@inproceedings{096f9bf05ce04bc9920c04185a8d7e35,
title = "A computational linguistic study of personal recovery in bipolar disorder",
abstract = "Mental health research can benefit increasingly fruitfully from computational linguistics methods, given the abundant availability of language data in the internet and advances of computational tools. This interdisciplinary project will collect and analyse social media data of individuals with bipolar disorder with regard to their recovery experiences. Personal recovery - living a satisfying and contributing life along symptoms of severe mental illnesses - so far has only been investigated qualitatively with structured interviews and quantitatively with standardised questionnaires with mainly English-speaking participants in Western countries. Complementary to this evidence, computational linguistic methods allow us to analyse first-person accounts shared online in large quantities, representing unstructured settings and a more heterogeneous, multilingual population, to draw a more complete picture of the aspects and mechanisms of personal recovery in bipolar disorder.",
author = "Glorianna Jagfeld",
year = "2019",
month = jul,
day = "31",
doi = "10.18653/v1/P19-2003",
language = "English",
booktitle = "Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop",
publisher = "Association for Computational Linguistics",
note = "ACL Student Research Workshop (SRW) : The 57th Annual Meeting of the Association for Computational Linguistics (ACL) , ACL SRW 2019 ; Conference date: 28-07-2019 Through 02-08-2019",
url = "https://sites.google.com/view/acl19studentresearchworkshop/",

}

RIS

TY - GEN

T1 - A computational linguistic study of personal recovery in bipolar disorder

AU - Jagfeld, Glorianna

PY - 2019/7/31

Y1 - 2019/7/31

N2 - Mental health research can benefit increasingly fruitfully from computational linguistics methods, given the abundant availability of language data in the internet and advances of computational tools. This interdisciplinary project will collect and analyse social media data of individuals with bipolar disorder with regard to their recovery experiences. Personal recovery - living a satisfying and contributing life along symptoms of severe mental illnesses - so far has only been investigated qualitatively with structured interviews and quantitatively with standardised questionnaires with mainly English-speaking participants in Western countries. Complementary to this evidence, computational linguistic methods allow us to analyse first-person accounts shared online in large quantities, representing unstructured settings and a more heterogeneous, multilingual population, to draw a more complete picture of the aspects and mechanisms of personal recovery in bipolar disorder.

AB - Mental health research can benefit increasingly fruitfully from computational linguistics methods, given the abundant availability of language data in the internet and advances of computational tools. This interdisciplinary project will collect and analyse social media data of individuals with bipolar disorder with regard to their recovery experiences. Personal recovery - living a satisfying and contributing life along symptoms of severe mental illnesses - so far has only been investigated qualitatively with structured interviews and quantitatively with standardised questionnaires with mainly English-speaking participants in Western countries. Complementary to this evidence, computational linguistic methods allow us to analyse first-person accounts shared online in large quantities, representing unstructured settings and a more heterogeneous, multilingual population, to draw a more complete picture of the aspects and mechanisms of personal recovery in bipolar disorder.

U2 - 10.18653/v1/P19-2003

DO - 10.18653/v1/P19-2003

M3 - Conference contribution/Paper

BT - Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop

PB - Association for Computational Linguistics

T2 - ACL Student Research Workshop (SRW)

Y2 - 28 July 2019 through 2 August 2019

ER -