Merchandising/Marketing/Retailing: Management

Representation of Plus-Size Fashion Models in Academic Research: A Text Mining Analysis of Size-Inclusivity 

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Abstract

This study employs text mining to scrutinize academic discourse surrounding the representation of plus-size models, revealing its implications for inclusivity and body positivity in both the fashion industry and academia. By analyzing scholarly articles from the past two decades using natural language processing and Latent Dirichlet Allocation, we identify significant themes and research gaps. Our findings indicate seven primary topics, ranging from positive body image effects and self-evaluation to the challenges of diversity in fashion and health-related issues tried to industry-imposed beauty standards. Despite a growing emphasis on size inclusivity, the industry's hesitance due to profit motives suggests a significant barrier to embracing diversity. Our analysis advocates for ongoing research to bridge the gap between consumer expectations and industry practices, aiming to create a more inclusive fashion landscape that celebrates all body types and counters the detrimental effects of narrow beauty ideals. 

Keywords: Size-inclusivity, Text-mining analysis, Topic modeling, Fashion advertising, Plus-size fashion model, Plus-size fashion advertising

How to Cite:

Yang, S., Kim, S. & Seo, S., (2025) “Representation of Plus-Size Fashion Models in Academic Research: A Text Mining Analysis of Size-Inclusivity ”, International Textile and Apparel Association Annual Conference Proceedings 81(1). doi: https://doi.org/10.31274/itaa.18530