Stylistic analysis of Telegram channel vocabulary (group of terms / group of slang)

this study is devoted to a stylistic analysis of the vocabulary of Telegram channels, focusing on the interaction between terminological vocabulary and slang terms. The introduction substantiates the relevance of studying language dynamics in Telegram as an environment where vocabulary is transformed under the influence of sociolinguistic factors, globalization, and English borrowings (e.g., reach, engagement rate). The author emphasizes the role of channel themes in forming unique stylistic patterns that combine professional terms with expressive elements to attract the audience. The Materials and Methods section describes the criteria for analysis: target audience, thematic orientation (finance, IT, lifestyle), and the frequency of use of terms and slang. Special attention is paid to the strategies of the authors – from adhering to literary norms to deliberately breaking them to create an informal tone. Trends towards abbreviations ("chel", "chill") and borrowings that form the "micro-styles" of the channels have been identified. The results demonstrate a predominance of mixed vocabulary (over 45% in all themes), confirming a balance between the precision of terms and the expressiveness of slang. In technical channels (ML/AI, DevOps), terminology constitutes up to 90% of the vocabulary, whereas in game design and "other themes" slang dominates (24-27%). Emotionally charged units (for example, "ulet" – 8.77 on the expressiveness scale) enhance engagement, while Anglicisms (backend, API) remain unadapted. Frequency tables illustrate the leadership of technical terms (backend – 97.04 occurrences) and high variability in the spelling of slang terms ("prereliz" – 4.26% errors). The discussion underlines the functions of vocabulary: creating group identity, emotional impact, and content virality. Closed channels form unique "lexical codes," while open channels influence overall language trends. In the conclusion, the author notes the contextual dependence of vocabulary, the necessity of taking into account irony, visual elements (emoji), and the dynamics of channel development. Prospects for future research include the analysis of jargon migration between platforms and the application of corpus linguistics methods.

Telegram channels, terminological vocabulary, slang, stylistic analysis, language dynamics