Layers of Folkloric Variation: Computational Explorations of Poetic and Narrative Text Corpora

Author:

Sarv Mari, ,Järv Risto,

Abstract

Variation is a core feature of folklore that plays a part in configuring the processes of folkloric communication, transmission and creativity. Computational analysis of large folklore collections offers new outlooks on the study of variation. The article explores the nature of folkloric variation on the basis of folk song and fairy tale text corpora from the Estonian Folklore Archives. Our enquiry into regional variation in Estonian folk song showed different patterns of geographic variation for metre, repertoire and language. To investigate further the possibilities to disassemble the components of variation we turned to a smaller corpus of fairy tale texts from the distinct Seto language community. The results of stylometric analysis of fairy tales collected within the close language community as a rule found that word usage patterns in stories told by the same storytellers were closer to each other than stories with the same content (i.e. tale types). However, other factors, such as collectors’ individual styles, recording time, length of text, and storyteller’s place of origin contributed notably to similarity as per stylometric scores. The study has shown that the individual features and aspects of such a complex phenomenon as folklore can follow its own variation patterns. Computational analysis of the variation in large text corpora helps us get a better understanding of the functioning of variation, and the processes of folkloric creation. However, the layers of folkloric variation are not that easy to disassemble, one must be aware of the biases in text corpora and keep in mind the effect of the linguistic variation on the results.

Publisher

Estonian Literary Museum Scholarly Press

Subject

Anthropology,Cultural Studies

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Anlatıcının İcrası Sürecinde Varyantlar;Kültür Araştırmaları Dergisi;2024-08-24

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