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Using Social Media Analytics for Extracting Fashion Trends of Preowned Fashion Clothes

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Advances in Intelligent Manufacturing and Service System Informatics (IMSS 2023)

Part of the book series: Lecture Notes in Mechanical Engineering ((LNME))

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Abstract

In recent years, the cloth industry has faced fast fashion trends. This has resulted in Fast fashion as a supply chain model for clothing and accessories that is supposed to respond quickly to the latest fashion trends by frequently updating the products already available in the inventory. However, Fast Fashion has created serious challenges for the sustainability of the clothing industry. This paper investigates the use of social media analytics to understand fashion trends in the preowned fashion industry. The study aims to establish a link between environmental pollution and fast fashion by investigating the preowned fashion industry from both consumer and business perspectives. To achieve this, the study proposes a social analytics (SA) approach to analyze social media posts and predict preowned fashion trends. By using SA techniques, the study hopes to provide valuable insights into consumer behavior and preferences in the preowned fashion industry, which can be used to promote sustainable fashion practices and reduce environmental pollution. Overall, the study demonstrates the potential of social media analytics in understanding and predicting fashion trends, with the goal of promoting sustainable fashion practices.

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Authors and Affiliations

  1. School of Business, Social and Decision Sciences, Constructor University, Campus Ring 1, 28759, Bremen, Germany

    Noushin Mohammadian, Nusrat Jahan Raka, Meriel Wanyonyi, Yilmaz Uygun & Omid Fatahi Valilai

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  1. Noushin Mohammadian
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  2. Nusrat Jahan Raka
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  3. Meriel Wanyonyi
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  4. Yilmaz Uygun
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  5. Omid Fatahi Valilai
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Corresponding author

Correspondence to Omid Fatahi Valilai .

Editor information

Editors and Affiliations

  1. Istanbul Medipol University, Istanbul, Türkiye

    Zekâi Şen

  2. Department of Industrial Engineering, Sakarya University, Serdivan, Sakarya, Türkiye

    Özer Uygun

  3. Faculty of Applied Sciences, Sakarya University of Applied Sciences, Kaynarca, Sakarya, Türkiye

    Caner Erden

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Mohammadian, N., Raka, N.J., Wanyonyi, M., Uygun, Y., Fatahi Valilai, O. (2024). Using Social Media Analytics for Extracting Fashion Trends of Preowned Fashion Clothes. In: Şen, Z., Uygun, Ö., Erden, C. (eds) Advances in Intelligent Manufacturing and Service System Informatics. IMSS 2023. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-99-6062-0_15

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  • DOI: https://doi.org/10.1007/978-981-99-6062-0_15

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-6061-3

  • Online ISBN: 978-981-99-6062-0

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