Analysis of Properties of Fashion Trading Areas Using Network Analysis Technique

Kim, Yun-Jeong; Lee, Joeun; Lee, Yuri

doi:10.5850/jksct.2016.40.2.203

Cited by 9 publications

(1 citation statement)

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“…Semantic network analysis is a method of recognizing a word constituting a text as a point (node), connecting the relation between nodes by a line, and grasping the meaning using a visualized connection network [74]. Network analysis is widely used as a method of research in fashion and marketing, as it allows researchers to analyze individuals' opinions and ideas posted on unstructured online boards [66,75,76].…”

Section: Analyticla Methodsmentioning

confidence: 99%

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

Youn

Jung

2021

Sustainability

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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.

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Section: Analyticla Methodsmentioning

confidence: 99%