The Vocabulary of Modern Technologies: From “Blockchain” to “Metaverse”

Modern technologies enter public speech with a noticeable vocabulary trail: terms coined in developer spaces later circulate through marketing copy, news coverage, and everyday conversation. A recurring puzzle follows this trajectory–some technical labels stabilize into ordinary nouns, while others remain contested, shift in meaning, or split into separate “technical” and “popular” senses. The project addresses how this migration happens for high-visibility technologies, using the contrast between terms such as “blockchain” and “metaverse” and the way they are interpreted at different stages of adoption.

The study aims to explain how technology vocabulary evolves as terms travel across communities and channels. It seeks to systematize the kinds of word-making processes and semantic shifts involved in borrowing, compounding, acronyms, metaphor, and related naming patterns. It also sets out to compare term behavior across selected domains, to identify which definitional properties and narrative frames recur, and to trace how pragmatic functions–persuasion, expertise signaling, and community alignment–shape meaning in context.

The object of the study is the language used to describe and promote modern technologies, observed across corpora drawn from technical and public-facing sources. The subject of the study covers the set of lexical items and multiword phrases that migrate during technology diffusion–together with their formation mechanisms, semantic changes, and discourse patterns. Particular attention falls on how terms such as “blockchain,” “token,” “smart contract,” “web3,” “metaverse,” “digital twin,” and “avatar” acquire and revise meanings through repeated use.

To capture vocabulary evolution in motion, the research combines data collection from technical documentation, developer blogs, product pages, news reporting, and social media discourse. A sampling strategy across time tracks emergence and stabilization, while term-candidate extraction and frequency-by-context measures show which words gain traction and how their immediate neighbors change as audiences expand.

A conceptual taxonomy organizes the material by separating core technical terms, marketing and branding expressions, and hybrid socio-technical phrases that move between these registers. The analysis links naming mechanisms–borrowing, compounding, metaphor, acronym expansion–to semantic change processes such as narrowing, broadening, and rebranding, enabling comparisons of definitional status across technologies rather than treating all terms as equivalent.

Meaning construction is then examined through linguistic and discourse tools focused on metaphors and promise-oriented language, including frames like decentralization and immersion. Cross-domain comparisons follow the same target terms across different definitional contests and collocation profiles, while cross-lingual and socio-cultural observations consider how translation strategies (loanwords, calques, transliteration, and adaptation) and community differences (developers, investors, general audiences) influence which labels become dominant. The synthesis brings these observations together into an explanatory model of how early technical naming develops into widely recognizable vocabulary and highlights pathways for extending the dataset to additional technologies, languages, and time periods.