Abstract
Word category arcs measure the progression of word usage across a story. Previous work on arcs has explored structural and psycholinguistic arcs through the course of narratives, but so far it has been limited to English narratives and a narrow set of word categories covering binary emotions and cognitive processes. In this paper, we expand over previous work by (1) introducing a novel, general approach to quantitatively analyze word usage arcs for any word category through a combination of clustering and filtering; and (2) exploring narrative arcs in literature in eight different languages across multiple genres. Through multiple experiments and analyses, we quantify the nature of narratives across languages, corroborating existing work on monolingual narrative arcs as well as drawing new insights about the interpretation of arcs through correlation analyses.
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CITATION STYLE
Wu, W., Wang, L., & Mihalcea, R. (2023). Word Category Arcs in Literature Across Languages and Genres. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (pp. 36–47). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2023.wnu-1.6
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