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Semantic Network Analysis to Explore the Concept of Sustainability in the Apparel and Textile Industry

Author

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  • Chorong Youn

    (Department of Textiles, Merchandising and Fashion Design, Seoul National University, Seoul 08826, Korea)

  • Hye Jung Jung

    (Da Vinci College of General Education, Chung-Ang University, Seoul 06974, Korea)

Abstract

Consumers are becoming increasingly aware and sensitive to the negative environmental impact caused by the fashion industry and by consumers’ high consumption of fashion. This study analyzes people’s unfiltered comments and behaviors on social media sites related to the sustainability of fashion products. Recently, the number of social media data, called big data, has exploded, transcending the level that can be analyzed with existing tools. This study aims to identify consumers’ perceptions of sustainable fashion using the search words “sustainable fashion” to examine public opinion trends found in SNS big data. Text mining was employed to extract meaningful words from the SNS texts using semantic network analysis to analyze the connectivity and propagation trends. The text data were collected from Facebook using the Google search engine to detect tendencies in the occurrence of keywords related to sustainable fashion in SNS over the past five years (2016~2020). The results revealed that the keywords “eco-friendly”, “ethical”, and “recycle” had the highest frequency and centrality. As a result of grouping the keywords based on their correlations, sustainable fashion texts from the SNS data could be classified into four groups: “supply chain of sustainable fashion”, “circular fashion”, “fashion business concepts for sustainability”, and “academic importance of sustainable fashion”. This study strengthens the extent of research by using SNS big data and provides guidelines for product development and communication strategies for a sustainable fashion industry based on customers’ meaningful opinions.

Suggested Citation

  • Chorong Youn & Hye Jung Jung, 2021. "Semantic Network Analysis to Explore the Concept of Sustainability in the Apparel and Textile Industry," Sustainability, MDPI, vol. 13(7), pages 1-17, March.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:7:p:3813-:d:526959
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    1. Nornajihah Nadia Hasbullah & Zuraidah Sulaiman & Adaviah Mas’od & Hanis Syuhada Ahmad Sugiran, 2022. "Drivers of Sustainable Apparel Purchase Intention: An Empirical Study of Malaysian Millennial Consumers," Sustainability, MDPI, vol. 14(4), pages 1-24, February.
    2. Xue, Zhebin & Li, Qing & Zeng, Xianyi, 2023. "Social media user behavior analysis applied to the fashion and apparel industry in the big data era," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).
    3. Tatjana Mamula Nikolić & Ivan Paunović & Mirjana Milovanović & Nenad Lozović & Marija Đurović, 2022. "Examining Generation Z’s Attitudes, Behavior and Awareness Regarding Eco-Products: A Bayesian Approach to Confirmatory Factor Analysis," Sustainability, MDPI, vol. 14(5), pages 1-16, February.
    4. Ana La Rosa & Jennifer Johnson Jorgensen, 2021. "Influences on Consumer Engagement with Sustainability and the Purchase Intention of Apparel Products," Sustainability, MDPI, vol. 13(19), pages 1-15, September.
    5. Fuzhong Chen & Shakil Ahmad & Guohai Jiang & Jinwei Chen, 2023. "Factors Affecting Textiles Products Exports of Major Producers: A Gravity Model Approach," SAGE Open, , vol. 13(4), pages 21582440231, December.

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