Maciej Janicki - Large-scale weighted sequence alignment for the study of intertextuality in Finnic oral folk poetry

jdmdh:11390 - Journal of Data Mining & Digital Humanities, August 13, 2023, NLP4DH - https://doi.org/10.46298/jdmdh.11390
Large-scale weighted sequence alignment for the study of intertextuality in Finnic oral folk poetryArticle

Authors: Maciej Janicki ORCID1

The digitization of large archival collections of oral folk poetry in Finland and Estonia has opened possibilities for large-scale quantitative studies of intertextuality. As an initial methodological step in this direction, I present a method for pairwise line-by-line comparison of poems using the weighted sequence alignment algorithm (a.k.a. ‘weighted edit distance’). The main contribution of the paper is a novel description of the algorithm in terms of matrix operations, which allows for much faster alignment of a poem against the entire corpus by utilizing modern numeric libraries and GPU capabilities. This way we are able to compute pairwise alignment scores between all pairs from among a corpus of over 280,000 poems. The resulting table of over 40 million pairwise poem similarities can be used in various ways to study the oral tradition. Some starting points for such research are sketched in the latter part of the article.


Volume: NLP4DH
Published on: August 13, 2023
Accepted on: July 6, 2023
Submitted on: May 29, 2023
Funding:
    Source : OpenAIRE Graph
  • Formulaic intertextuality, thematic networks and poetic variation across regional cultures of Finnic oral poetry / Consortium: FILTER; Funder: Academy of Finland; Code: 333138

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