IDEAS home Printed from https://ideas.repec.org/p/hig/wpaper/77-lng-2018.html
   My bibliography  Save this paper

A Data Analysis Tool for the Corpus of Russian Poetry

Author

Listed:
  • Olga Lyashevskaya

    (National Research University Higher School of Economics)

  • Kristina Litvintseva

    (National Research University Higher School of Economics)

  • Ekaterina Vlasova

    (National Research University Higher School of Economics)

  • Eugenia Sechina

    (National Research University Higher School of Economics)

Abstract

A data analysis tool of the Corpus of Russian Poetry (a part of the Russian National Corpus) is designed for quantitative research in various areas of versology and linguistics aspects of the poetic texts. The core part, a frequency database of the corpus, includes annotation at the level of texts, verses, words as well as patterns of words, letters, and stress. The tool allows a user to study certain properties (e. g. rhyming patterns, lexical co-occurrence) taken alone and in their interaction, both in the whole corpus and in subcorpora. Besides that, it facilitates the contrastive studies of two chosen subcorpora. The paper reports a few case studies demonstrating applicable descriptive and exploratory methods and potential for further research in the field of the digital literary studies

Suggested Citation

  • Olga Lyashevskaya & Kristina Litvintseva & Ekaterina Vlasova & Eugenia Sechina, 2018. "A Data Analysis Tool for the Corpus of Russian Poetry," HSE Working papers WP BRP 77/LNG/2018, National Research University Higher School of Economics.
  • Handle: RePEc:hig:wpaper:77/lng/2018
    as

    Download full text from publisher

    File URL: https://wp.hse.ru/data/2018/12/29/1143017363/77LNG2018.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    poetic corpora; quantitative linguistics; lexical markers; lexical diversity; rhyme; linguistic poetics; versology; Russian language; Russian National Corpus;
    All these keywords.

    JEL classification:

    • Z - Other Special Topics

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hig:wpaper:77/lng/2018. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Shamil Abdulaev or Shamil Abdulaev (email available below). General contact details of provider: https://edirc.repec.org/data/hsecoru.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.