Sustainability and Social Responsibility

Semantic Shifts in Sustainability Discourse: A Study of Fair-Trade Clothing Market 

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Abstract

This study examines the evolution of fair-trade clothing discourse by analyzing semantic shifts between 2019 and 2024. Using big data methodology, 3,000 (2019) and 3,301 (2024) online reviews were collected via Google Custom Search API and processed through Python-based text mining and semantic network analysis. Lexical frequency analysis revealed significant increases in core terminology: "fashion" (838→960), "fair" (566→834), and "sustainable" (440→769). Semantic network visualization demonstrated structural evolution from separated ethical-commercial domains in 2019 toward integrated consumer-oriented framing in 2024. Labor-focused terminology gained prominence, indicating enhanced market emphasis on production ethics. The comparative analysis reveals a market transformation from niche ethical positioning to mainstream commercial integration across five dimensions: ethical-consumer alignment, sustainability-aesthetics convergence, product category expansion, retail accessibility, and labor transparency. These findings offer retailers actionable insights for integrating sustainability with consumer appeal in competitive markets.

Keywords: Fair-Trade Clothing, Sustainable Fashion, Text Mining, Semantic Network Analysis, Consumer Discourse, Ethical Consumption

How to Cite:

Sheikh, M. & Su, J., (2025) “Semantic Shifts in Sustainability Discourse: A Study of Fair-Trade Clothing Market ”, International Textile and Apparel Association Annual Conference Proceedings 82(1). doi: https://doi.org/10.31274/itaa.21743