The growing supply of online mental health tools, platforms and treatments results in an enormous quantity of digital narrative data to be structured, analysed and interpreted. Natural Language Processing is very suitable to automatically extract textual and structural features from narratives. Visualizing these features can help to explore patterns and shifts in text content and structure. In this study, streamgraphs are developed for different types of "Letters from the Future", an online mental health promotion instrument. The visualizations show differences between as well as within the different letter types, providing directions for future research in both the visualization of narrative structure and in the field of narrative psychology. The method presented here is not limited to "Letters from the Future", the current object of study, but can in fact be used to explore any digital or digitalized textual source, like books, speech transcripts or email conversations.
|Title of host publication||7th Workshop on Computational Models of Narrative (CMN 2016)|
|Editors||Ben Miller, Antonio Lieto, Rémi Ronfard, Stephen G. Ware, Mark A. Finlayson|
|Place of Publication||Wadern|
|Publication status||Published - 2016|
|Publisher||Schloss Dagstuhl Leibniz-Zentrum für Informatik|