Weak Genres: Modeling Association Between Poetic Meter and Meaning in Russian Poetry

Abstract

This paper aims to formalize an established theory in versification studies known as ”semantic halo of a meter” which states that different metrical forms in modern poetry accumulate and retain distinct semantic associations. We use LDA topic modeling on a large-scale corpus of Russian poetry (1750-1950) to represent each poem in one topic space and then proceed to represent each meter as a distribution of aggregated topic probabilities. Using unsupervised classification and extensive sampling we show that robust form-meaning associations are present both within and between metrical forms: two samples of the same meter tend to appear most similar, while two metrical forms of the same family tend to group together. This effect is present if corpus is controlled for chronology and is not an artifact of population size. We argue that similar approach could be used to align and compare semantic halos across languages and traditions to give meaningful general-level answers to questions of literary history.