Казанский (Приволжский) федеральный университет, КФУ
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COMPARATIVE ANALYSIS OF LEXICAL DENSITY, LEXICAL DIVERSITY, AND MULTIWORD EXPRESSIONS IN RUSSIAN, ENGLISH, AND FRENCH LEGAL TEXTS: IMPLICATIONS FOR READABILITY AND UNDERSTANDABILITY
Форма представленияСтатьи в российских журналах и сборниках
Год публикации2025
Языканглийский
  • Марико Мохамед Ламин, автор
  • Библиографическое описание на языке оригинала Mariko M. Comparative analysis of lexical density, lexical diversity, and multiword expressions in Russian, English, and French legal texts: implications for readability and understandability / M. Mariko // Russian Linguistic Bulletin. — 2025. — № 7 (67). — URL: https://rulb.org/en/archive/7-67-2025-july/10.60797/RULB.2025.67.5. — DOI: 10.60797/RULB.2025.67.5
    Аннотация Lexical density is closely related to the notion of information packaging as content words in a text; therefore, texts with a higher proportion of content words are dense as they contain more information as opposed to texts that have a higher proportion of function words [10, P. 61–79]. Type-token ratio (TTR), also known as vocabulary size divided by text length, is a simple measure of lexical diversity. Lexical diversity refers to how varied the vocabulary used in a text is. For texts of similar length, the traditional type-token ratio can be used, which is the number of different words (types) in a text divided by the total number of words (tokens) [1, P. 185–207]. Multiword expressions refer to a diverse group of linguistic phenomena, connected by the fact that they do not fit neatly into the word-phrase dichotomy. Like phrases, they appear to be made up of multiple words. In our research, we analyzed text materials with lexical density, TTR, and multiword expressions from legal texts (texts of the United Nations). We compared the automatic analysis results to three linguistic measures in Russian, English, and French. A 60,000-word-based corpus was built for the analysis. Our research aimed at examining the lexical density, TTR, and multiword expressions of Russian, English, and French UN texts. To reach that goal, we used Rulingva, TextInspector, and LancsBox to compute our data. The results showed that the linguistic features selected for the investigation could impact complexity on account of lexical richness, being a multidimensional concept that encompasses several aspects of lexis use [12, P. 19].
    Ключевые слова French UN texts, English UN texts, Russian UN texts, TTR, lexical density, multi-word expressions, n-grams, readability.
    Название журнала Russian Linguistic Bulletin
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