REPRESENTATION OF GENDERED IDENTITY IN ENGLISH–UZBEK INFLUENCER DISCOURSE: AN AI-ENHANCED CORPUS STUDY
Keywords:
gendered identity; influencer discourse; AI-assisted corpus analysis; English–Uzbek comparison; digital communication.Abstract
This article investigates the representation of gendered identity in English–Uzbek influencer discourse through an AI-enhanced corpus-based approach. Drawing on a large bilingual corpus of influencer-generated content from Instagram, YouTube, and Telegram, the study explores how masculinity and femininity are discursively constructed across cultures. Using natural language processing (NLP) tools combined with qualitative discourse analysis, the research identifies lexical patterns, evaluative strategies, and pragmatic markers associated with gendered identity. The findings demonstrate clear cross-cultural differences: English influencer discourse emphasizes individualism, self-expression, and gender fluidity, while Uzbek influencer discourse foregrounds collectivist values, moral responsibility, and culturally grounded gender norms. The study confirms the effectiveness of AI-assisted corpus methods for uncovering ideological tendencies in digital discourse and contributes to gender studies, intercultural communication, and applied linguistics.
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