Using crowdsourcing to investigate perception of narrative similarity

For many applications measuring the similarity between documents is essential. However, little is known about how users perceive similarity between documents. This paper presents the first large-scale empirical study that investigates perception of narrative similarity using crowdsourcing. As a dataset we use a large collection of Dutch folk narratives. We study the perception of narrative similarity by both experts and non-experts by analyzing their similarity ratings and motivations for these ratings. While experts focus mostly on the plot, characters and themes of narratives, non-experts also pay attention to dimensions such as genre and style. Our results show that a more nuanced view is needed of narrative similarity than captured by story types, a concept used by scholars to group similar folk narratives. We also evaluate to what extent unsupervised and supervised models correspond with how humans perceive narrative similarity