Twitter is a social communication format on the internet that enables the exchange of common discourses through Twitter postings (Bucher 2019). These discourses can be grouped and organized through links, such as hashtags (Marx/Weidacher 2019). Twitter postings organized under a hashtag can be interpreted as emotional indices that express the author's views, opinions or group affiliation (Bucher 2019). In this way, experiences with illnesses can also be shared, such as experiences with depression by using the hashtag #depression: Individuals share their stories about their suffering or their current condition. The narrative of depression in the context of verbal interaction between therapist and patient has already been explored: patients focus both on symptoms and on their life situations (Karasz et al. 2012). Similar narratives can be found on Twitter, such as the narrative of the process of healing by fighting the illness or the narrative of hiding the disease. This contribution examines the narrative practices for experiencing depression on Twitter that are linked by the hashtag #depression. The data for this research project come from a corpus of publicly available Twitter postings (Pfaffenberger 2016). I employ the tools and methods of corpus linguistics in combination with an analysis of the narrative structure. The data have been anonymized and translated into English from the original German. References: Bucher, Hans-Jürgen (2019). Politische Meinungsbildung in sozialen Medien? Interaktionsstrukturen in der Twitter-Kommunikation. In: Marx, Konstanze/ Schmidt Axel (ed.): Interaktion und Medien. Heidelberg: Winter. 287-318. Karasz, Alison et al. (2012). What we talk about when we talk about depression: doctor–patient conversations and treatment decision outcomes. In: British Journal of General Practice, 62(594):e55-63. doi: 10.3399/bjgp12X616373. Marx, Konstanze/ Weidacher, Georg (2019). Internetlinguistik. Tübingen: Narr Francke Attempto. Pfaffenberger, Fabian (2016). Twitter als Basis wissenschaftlicher Studien. Eine Bewertung gängiger Erhebungs- und Analysemethoden der Twitter-Forschung. Wiesbaden: Springer.
