  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 diagnosed with
bipolar disorder with regard to their recovery experiences. Personal recovery -
living a satisfying and contributing life along symptoms of severe mental
health issues - 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.
