Trends in the development of new vocabulary in Russian-language texts 1991-2016
Bibliographic Data
| ID | 22150454 |
|---|---|
| Authors | Tatiana Alexandrovna Rychkova (0000-0002-0342-1308, corresponding author), Tatiana Aleksandrovna Rychkova (corresponding author) |
| Year | 2024 |
| Issue | 9 |
| Pages | 94-106 |
| Publication date | 2024-09-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Филология научные исследования (JOURNAL) |
| Journal identifiers | ISSN: 2454-0749 • E-ISSN: 2454-0749 |
| Publisher | Aurora Group, s.r.o (PUBLISHER) |
| DOI | 10.7256/2454-0749.2024.9.71769 |
| OpenAlex | W4403499411 |
| Language | EN |
| References cited | 2 |
The article is devoted to the analysis of the dynamics of the lexical system of the Russian language in the period from 1991 to 2016. The analysis showed that in the vocabulary with sharply increased popularity, there is a predominance of nouns and adjectives, which indicates a tendency to increase their use. At the same time, the frequency of using other parts of speech remains stable or decreases. The study also revealed that neologisms can significantly increase their frequency of use in the context of new socio-historical realities. Special attention is paid to the derived forms of established words, which have a high probability of increasing popularity compared to root words. It was revealed that topics related to economics and finance were more significant for Russians in the period under review than terms related to new realities such as the Internet. Finally, the study focuses on a large number of words with pejorative coloring, reflecting financial problems and social difficulties, which indicates the negative aspects of life in the post-Soviet period and their impact on language. To analyze lexical changes, an innovative method of automatic selection of lexical neoplasms was used, developed within the framework of the project "Automatic detection of lexical changes". The application of this method represents a significant improvement over traditional approaches based on manual search in various sources. Unlike previously used methods, this study uses a method of automatic text processing using a specially developed Python program. Using this program, a 1992-2016 file consisting of 70,498,699 words was analyzed. From this file, words were selected whose frequency of use increased by 1000% and were used more than 1000 times, which made it possible to identify the most significant and popular lexical units in the life of the country during the period under review. Based on this volumetric sample and machine counting, the most objective results were obtained, which allows not only to identify new and outdated words, but also to track general trends in the use of vocabulary. This is the first time a project of this type is being implemented in Russia
Linguistics · Vocabulary · Discourse Analysis and Cultural Communication · History · Philosophy
| Highly cited | No |
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