A computational linguistic study of personal recovery in bipolar disorder

Jagfeld, Glorianna (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. Association for Computational Linguistics, ITA.

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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.

Item Type:
Contribution in Book/Report/Proceedings
ID Code:
142140
Deposited By:
Deposited On:
06 Mar 2020 11:25
Refereed?:
Yes
Published?:
Published
Last Modified:
16 Jun 2020 07:16