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We continue the study of the reproducibility of Propp’s annotations from Bod et al. (2012). We present four experiments in which test subjects were taught Propp’s annotation system; we conclude that Propp’s system needs a significant amount of training, but that with sufficient time investment, it can be reliably trained for simple tales.
A formal narrative representation is a procedure assigning a formal description to a natural language narrative. One of the goals of the computational models of narrative community is to understand this procedure better in order to automatize it. A formal framework fit for automatization should allow for objective and reproducible representations. In this paper, we present empirical work focussing on objectivity and reproducibility of the formal framework by Vladimir Propp (1928). The experiments consider Propp’s formalization of Russian fairy tales and formalizations done by test subjects in the same formal framework; the data show that some features of Propp’s system such as the assignment of the characters to the dramatis personae and some of the functions are not easy to reproduce.
Interested in formally modelling similarity between narratives, we investigate judgements of similarity between narratives in a small corpus of film reviews and book–film comparisons. A main finding is that judgements tend to concern multiple levels of story representation at once. As these texts are pragmatically related to reception contexts, we find many references to reception quality and optimality. We conclude that current formal models of narrative can not capture the task of naturalistic narrative comparisons given in the analysed reviews, but that the development of models containing a more reception-oriented point of view will be necessary.