Linguistic Resources Topic Models for the Analysis of Persian Poems

摘要

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 analysis step, we obtained very interesting and meaningful results regarding the correlation between poets and topics, their evolution through time, as well as the correlation between the topics and the metre used in the poems. This work should thus provide valuable results to literature researchers, especially for those working on stylistics or comparative literature.