This article examines how social media platforms accelerate and redirect the semantic evolution of English words. The relevance of the study lies in the fact that digital communication has become the primary environment in which new word senses first emerge, spread and stabilize, while traditional accounts of semantic change were developed for slower, print-mediated processes and do not fully capture the speed and mechanisms of change observed online. The aim of the research is to identify the principal types of semantic change operating in social media English and to relate them to the platform features that drive them. The material comprises peer-reviewed studies on lexical semantic change detection, sociolinguistic accounts of digital communication, and corpus-based analyses of emoji and hashtag meaning, illustrated with attested social-media word senses. Descriptive, comparative and componential analysis methods were applied, together with a qualitative review of documented case items. The results show that four mechanisms recur most frequently: semantic broadening, semantic narrowing, metaphorical extension, and pragmatic-emotive shift, each linked to identifiable platform affordances such as brevity constraints, virality, visual-textual hybridity, and community-specific register. The discussion situates these findings within classical semantic-change theory and computational change-detection research, showing continuity as well as genuine novelty in the digital context. The practical value of the study lies in its applicability to lexicography, corpus linguistics and English-language teaching materials that address contemporary usage.

semantic change, social media, English lexicon, semantic broadening, semantic narrowing, metaphorical extension, emoji semantics, hashtag, sociolinguistics, corpus linguistics.

N.Tahmasebi, L.Borin, and A.Jatowt, “Survey of computational approaches to lexical semantic change detection,” arXiv:1811.06278, 2019.

A.Robertson, F.F.Liza, D.Nguyen, B.McGillivray, and S.A.Hale, “Semantic journeys: Quantifying change in emoji meaning from 2012–2018,” Utrecht University Repository, 2021.

C.Ilbury, “Social media and sociolinguistic change,” presented at UK Language Variation and Change Conf. (UKLVC15), Lancaster Univ., 2025.

A.Blank, “Words and concepts in time: Towards diachronic cognitive onomasiology,” metaphorik.de, no. 01/2001, pp. 6–25, 2001.

N.Baes, N.Haslam, and E.Vylomova, “A multidimensional framework for evaluating lexical semantic change with social science applications,” arXiv:2406.06052, 2024.

M.A.Boukhaled, B.Fagard, and T.Poibeau, “The dynamics of semantic change: A corpus-based analysis,” in Proc. 11th Int. Conf. Agents and Artificial Intelligence (ICAART), Lecture Notes in Artificial Intelligence, vol. 11978, 2019, pp. 1–15.

L.L.Panjaitan and A.N.Patria, “Social media and language evolution: The impact of digital communication on language change,” Int. J. Linguistics, Literature and Translation, vol. 7, no. 12, pp. 53–57, 2024.

G.Donoso and D.Sánchez, “Dialectometric analysis of language variation in Twitter,” in Proc. 4th Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial), 2017, pp. 16–25.

P.Shoemark, “Discovering and analysing lexical variation in social media text,” Ph.D. dissertation, School of Informatics, Univ. of Edinburgh, 2020.

A.S.Calude, M.Long, and J.Burnette, “#AreHashtagsWords? Structure, position, and syntactic integration of hashtags in (English) tweets,” Linguistics Vanguard, vol. 10, no. 1, pp. 105–114, 2024.