CORPUS-ASSISTED COGNITIVE ANALYSIS OF EMERGING PERSONALITY VOCABULARY IN SOCIAL MEDIA

The rapid expansion of social media has significantly transformed the way individuals express personality, emotions, and identity. Platforms such as X (formerly Twitter), Instagram, TikTok, and Facebook have introduced a dynamic environment in which new personality-related vocabulary continuously emerges and evolves. Words such as authentic, toxic, introvert, woke, resilient, gaslighter, and people-pleaser have become increasingly common in online communication, reflecting changes in social attitudes and cultural values. This paper explores emerging personality vocabulary from the perspectives of Cognitive Linguistics and Corpus Linguistics. The study proposes a corpus-assisted framework for identifying, classifying, and interpreting newly popular personality expressions in English social media discourse. Drawing upon cognitive theories of categorization and conceptualization, the paper discusses how personality vocabulary represents changing social identities and conceptual structures. Corpus linguistic techniques, including frequency analysis, concordance, collocation, and semantic preference, are presented as effective tools for examining lexical patterns in large collections of social media texts. The study argues that combining cognitive linguistic theories with corpus-assisted methods provides a comprehensive understanding of how personality vocabulary develops in digital communication. The proposed framework contributes to contemporary linguistic research by highlighting the interaction between language, cognition, and online culture while offering practical implications for discourse analysis, lexicography, and language education.