A topic modelling tool, which was originally developed for performing text analysis on very short texts written in English, was adapted to the text genre of Swedish folk legends. The topic modelling tool was configured to use a word space model trained on a Swedish corpus, as well as a Swedish stop word list. The stop word list consisted of standard Swedish stop words, as well as 380 additional stop words that were tailored to the content of the corpus and therefore also included older spelling versions and grammatical forms of Swedish words. The adapted version of the tool was applied on a corpus consisting of around 10,000 Swedish folk legends, which resulted in the automatic extraction of 20 topics. Future versions of the tool will be extended with text summarisation func- tionality, in order to retain the text overview provided by the tool also when it is applied on longer folk legends.