This paper describes the usage of Natural Language Processing tools, mostly probabilistic topic modeling, to study semantics (word correlations) in a collection of Persian poems consisting of roughly 18k poems from 30 different poets. For this study, we put a lot of effort in the preprocessing and the development of a large scope lexicon supporting both modern and ancient Persian. In the analys...

We apply topic modeling to classifying the genre of Ghazal, a form common in Persian poetry. We show that a classifier based on automatically-generated topics exposes important information with only a small performance penalty: the top discriminative topics can be manually aligned with themes prevalent in the associated genres, as identified by scholars of literature. We also weigh in on a long...

The article focuses on the role of keywords, their statistical data for determining thematic dominance when working with large arrays texts. description is based materials a typological linguistic study texts military songs, period 1939-1945, in English and Russian. selection keywords was carried out basis semantic, lexical-syntactic, morphological analysis, taking into account frequency use. u...