Kseniya Tveryanovich’s scientific contributions

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Publications (1)


Figure 1: Areas of knowledge in the domain model
Figure 1: Distribution of stressed metrical positions per line in the complete poetic works of Garcilaso, Herrera, Góngora, and Lope
Figure 1: Average observed length of stanza sequences with the same rhyme endings compared with expected length based on a random distribution of all stanzas
Figure 1: The 20 most common topolexes (content words only) and their recurrence plotted on a logarithmic scale
Figure 1: The main dialects of the Finnic languages at the beginning of the 20th century (Grünthal forthcoming)

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Tackling the Toolkit
  • Book
  • Full-text available

January 2021

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Kseniya Tveryanovich

In Tackling the Toolkit, we focus on the methodological innovations, challenges, obstacles and even shortcomings associated with applying quantitative methods to poetry specifically and poetics more broadly. Using tools including natural language processing, web ontologies, similarity detection devices and machine learning, our contributors explore not only metres, stanzas, stresses and rhythms but also genres, subgenres, lexical material and cognitive processes. Whether they are testing old theories and laws, making complex concepts machine-readable or developing new lines of textual analysis, their works challenge standard descriptions of norms and variations.

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