Evaluative Language in High-Stakes Public Speaking: A Corpus Analysis of Miss Universe Q&A Sessions - Le, Long Viet; Vo, Lien-Huong (Journal of Digital Sociohumanities, 2025)
This paper is part of a broader research project examining evaluative language in the high-stakes public speaking context of the Miss Universe (MU) pageant, contributing to our understanding of spontaneous speech patterns. It investigates the evaluative language patterns employed by MU candidates during the Q&A sessions, utilizing Appraisal Theory as a framework for analysis. The primary aim was to uncover the common patterns of evaluative language used by the candidates during such pivotal moments. Data were collected from MU Q&A sessions between 2000 and 2023, focusing on English-speaking candidates’ responses. Using Sketch Engine for corpus analysis, collocations and language patterns were extracted from 100 responses to analyze key linguistic elements. The results show a strong tendency toward positive evaluative language, particularly emphasizing themes of empowerment, inclusivity, and advocacy. These linguistic patterns reflect how candidates strategically employ language to project confidence, align with the ethos of the competition, and engage with global issues. Through their responses, candidates effectively use language to construct positive self-images and advocate for social change. These findings advance both theoretical and practical insights into the role of evaluative language in public speaking, offering implications for discourse analysis, corpus linguistics, and language use in media and performance contexts.