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Mental health research can benefit increasingly fruitfully from computationallinguistics methods, given the abundant availability of language data in theinternet and advances of computational tools. This interdisciplinary projectwill collect and analyse social media data of individuals diagnosed withbipolar disorder with regard to their recovery experiences. Personal recovery -living a satisfying and contributing life along symptoms of severe mentalhealth issues - so far has only been investigated qualitatively with structuredinterviews and quantitatively with standardised questionnaires with mainlyEnglish-speaking participants in Western countries. Complementary to thisevidence, computational linguistic methods allow us to analyse first-personaccounts shared online in large quantities, representing unstructured settingsand a more heterogeneous, multilingual population, to draw a more completepicture of the aspects and mechanisms of personal recovery in bipolar disorder.

A computational linguistic study of personal recovery in bipolar disorder