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Computer-Based Processing Of Literary Works And Study Of Literature

Author

Listed:
  • Vera G. Sibirtseva

    (National Research University Higher School of Economics)

Abstract

Currently many software applications that enable text analysis are being created for different purposes (semantic reference tools, concordancers, sentiment analysis etc.), but are not being used by literary researchers. Computer software allows to facilitate the search of required information and to considerably save time. With such an approach to the field of linguistic and literary analysis – comparative analysis in particular – new opportunities and unexpected horizons are being offered. This paper suggests a critical review of existing computer resources related to text processing and a consistent description of program applications, successfully tested on literary materials and used for text analysis at the Faculty of Humanities (HSE Branch in Nizhny Novgorod): linguistic annotated text corpora; collections of literary texts of one author; different computer tools such as AntConc concordancer, multifunctional text analyzer LEKTA, LF aligner for text alignment – those tools which allow a variety of loaded and analyzed text collections. Computer-based text analysis shall be practiced only with further literary description and interpretation. This comparison of data retrieved in the process of computer-based analysis with existing traditional researches may mark the dawn of a new stage of literary text analysis.

Suggested Citation

  • Vera G. Sibirtseva, 2014. "Computer-Based Processing Of Literary Works And Study Of Literature," HSE Working papers WP BRP 07/LNG/2014, National Research University Higher School of Economics.
  • Handle: RePEc:hig:wpaper:07/lng/2014
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    File URL: http://www.hse.ru/data/2014/04/28/1322685391/07LNG2014.pdf
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    References listed on IDEAS

    as
    1. K. F. Lam & Hongqi Xue, 2005. "A semiparametric regression cure model with current status data," Biometrika, Biometrika Trust, vol. 92(3), pages 573-586, September.
    2. Sanjay Singh & S.R. Singh & Seema Sharma, 2017. "A partially backlogged EPQ model with demand dependent production and non-instantaneous deterioration," International Journal of Mathematics in Operational Research, Inderscience Enterprises Ltd, vol. 10(2), pages 211-228.
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    More about this item

    Keywords

    text analysis; linguistic corpora; concordancer; literary works; translation.;
    All these keywords.

    JEL classification:

    • Z19 - Other Special Topics - - Cultural Economics - - - Other

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