“Armenian” text of Russian poetry (interpretation of software data “Hypertext search for companion-words in author's texts”)

Автор: Pavlova Larisa V., Romanova Irina V.

Журнал: Новый филологический вестник @slovorggu

Рубрика: Русская литература

Статья в выпуске: 4 (55), 2020 года.

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The article presents the main results of the study of the corpus of poems created using the software system “Hypertext search for companion-words in author’s texts”, which allows you to automatically select repeating lexical combinations. Lexical combinations are word clusters passing from text to text, not necessarily interconnected by grammatical and verbal connections. The subject of this study was lexical combinations, including the “Armenia” component and cognates. We encountered two typical cases. The first is when a lexical combination unites poems by different authors, but there is no influence of one text on another (S. Gorodetsky and B. Chichibabin). The second case (V. Bryusov and S. Gorodetsky), when a lexical combination marks two texts, the analysis of which allows us to speak about the influence of Bryusov’s text on Gorodetsky. The use of the software package made it possible to identify a number of dominant components of the “Armenian” lexical combinations present in the verses of Russian poets (“Ararat”, “Yerevan”, “mountain”, “sky”, “earth”, “blood”, “heart”, “soul”, “flame”, “eternal”) and optional (“hostile”, “rot”, “myopic”, “book”, “child”, “Komitas”, etc.). During the interpretation of lexical combinations, textual “Armenian” associations of various authors were established (V Bryusov, S. Gorodetsky, O. Mandelstam, B. Sadovskoy, V Zvyagintsev, M. Shaginyan, M. Petrovych, B. Chichibabin, M. Dudina, B. Slutsky, M. Matusovsky, I. Lisnyanskaya and others), intertextual connections not previously recorded in the research literature were established.

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“armenian” text, lexical combinations, the software system “hypertext search for companion-words in author’s texts”, associative connections

Короткий адрес: https://sciup.org/149127272

IDR: 149127272   |   DOI: 10.24411/2072-9316-2020-00103

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