Ethical Fashion Research Trend Using Text Mining:Network Analysis of the Published Literature 2009-2019

Choi, Yeong-Hyeon; Lee, Kyu‐Hye

doi:10.5805/sfti.2020.22.2.181

Cited by 17 publications

(12 citation statements)

References 13 publications

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“…Vegan fashion prohibits all materials manufactured via animal abuse or animal exploitation, only allowing composite and plant materials instead of leather and fur materials [17]. Most studies state that vegan fashion emphasizes animal protection by prohibiting animal experiments and is related to other ethical aspects such as eco-friendly and social responsibilities [14,19]. Artificial fur is categorized as an ethical fashion product directed toward animal welfare since it replaces animal fur; moreover, the consumption of artificial fur--termed as ethical consumption--is judged as having the value of preserving the ecosystem and protecting animals [27].…”

Section: Environment and Usage Of Vegan Materialsmentioning

confidence: 99%

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Ethical Consumers’ Awareness of Vegan Materials: Focused on Fake Fur and Fake Leather

Choi

Lee

2021

Sustainability

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With an increase in ethical awareness, people have begun to criticize the unethical issues associated with the use of animal materials. This study focused on the transition of global consumers’ awareness toward vegan materials and the relationship between the interest in ethical subjects such as animals, the environment, and vegan materials. For this purpose, consumers’ posts about fur/fake fur and leather/fake leather uploaded on Google and Twitter from 2008 to 2019 were utilized, and the Term Frequency-Inverse Document Frequency (Tf-idf) value was extracted using Python 3.7. Furthermore, the worldwide Google keyword search volume of each word was analyzed using Smart PLS 3.0 to investigate global consumers’ awareness. First, with time, consumers began relating animal materials such as fur and leather to topics such as animal rights, animal abuse, and animal protection. Second, as interest in “animal welfare” increased, interest in “fake fur” also rose, and as interest in “cruelty free” increased, interest in “fake fur”, “vegan fur”, and “vegan leather” also increased. Third, as consumers’ interest in the “environment” increased, interest in vegan materials such as “fake fur” and “fake leather” decreased. However, as interest in “eco” increased, interest in “vegan leather” also augmented.

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Section: Environment and Usage Of Vegan Materialsmentioning

confidence: 99%

“…Although research on animal rights and animal welfare in the fashion industry is continuously increasing owing to the rise of social interest in ethical fashion, it is still far behind the research numbers of environmental and labor issues in the fashion industry [14]. Currently, vegan fashion attracts attention due to ethical fashion.…”

Section: Introductionmentioning

confidence: 99%

Ethical Consumers’ Awareness of Vegan Materials: Focused on Fake Fur and Fake Leather

Choi

Lee

2021

Sustainability

Self Cite

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“…Calculating the TF-IDF value results in the term "eco-friendly (690.90)" having the highest TF-IDF value. Since TF-IDF indicates the scarcity a word has in a sentence, a word with a higher TF-IDF value can be an important word [23,66]. This is because the word "eco-friendly" is not just a common term that people often use in the social media, but it is considered to be the core of the topic word in terms of "sustainable fashion" at the moment.…”

Section: Frequecy and Tf-idf Analysis Of Abstract Related To Sustainamentioning

confidence: 99%

“…On the quantitative research such as conducting consumer survey, the sampling issue has been issued as a limitation to investigate consumer behaviors [19], thus, decision-makers who are operating or plan to start a sustainable fashion business need an alternative of this limit. As an option of the sampling restrictions, recently, network analysis approaches using text mining methods from big data have been proposed to expand both quantitatively and qualitatively beyond the boundaries of accessibility to survey responses [20][21][22][23][24][25]. Applying the network analysis of text mining from massive volumes of user-created data, social sustainability [20,21], fashion [22], and fashion ethics studies [23,24] have been established.…”

Section: Introductionmentioning

confidence: 99%

“…As an option of the sampling restrictions, recently, network analysis approaches using text mining methods from big data have been proposed to expand both quantitatively and qualitatively beyond the boundaries of accessibility to survey responses [20][21][22][23][24][25]. Applying the network analysis of text mining from massive volumes of user-created data, social sustainability [20,21], fashion [22], and fashion ethics studies [23,24] have been established. Tehrani et al [25] indicated that the network analysis using text mining from big data of social media can analyze individuals' thoughts and extract meaningful information or predict trends in specific fields and they gathered user unstructured data collected on Twitter [25].…”

Section: Introductionmentioning

confidence: 99%

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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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Research trends of sustainability and marketing research, 2010–2020: Topic modeling analysis

Jung¹,

Kim²

2023

Heliyon

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Ethical Fashion Research Trend Using Text Mining:Network Analysis of the Published Literature 2009-2019

Cited by 17 publications

References 13 publications

Ethical Consumers’ Awareness of Vegan Materials: Focused on Fake Fur and Fake Leather

Ethical Consumers’ Awareness of Vegan Materials: Focused on Fake Fur and Fake Leather

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

Research trends of sustainability and marketing research, 2010–2020: Topic modeling analysis

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