Big data in fashion industry: Color cycle mining from runway data

Mei Yen Wong, Yilu Zhou, Heng Xu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Color is a powerful selling tool, especially in the fashion and textile industry, in which products aim to inspire consumers visually. Color Cycle Analysis studies the recurring cycle of trends. Traditional fashion color cycle analysis and prediction is performed by observing and extrapolating from trends apparent on fashion runways. With the emergence of big data, there is a potential to apply data analytics method in fashion industry. We propose and develop a data-driven methodology to analyze color trends by mining online textual data of global fashion runways collected from the Style.com website. By capturing three important elements in color hue, saturation and brightness, we are able effectively extract their presence and variations in textual data. We illustrate the reoccurrence of seven Color Cycle phases: High Chroma, Multicolored, Subdued, Earth Tones, Achromatic, and Purple Phase from runway review data.

Original languageEnglish (US)
Title of host publicationAMCIS 2016: Surfing the IT Innovation Wave - 22nd Americas Conference on Information Systems
PublisherAssociation for Information Systems
StatePublished - 2016
Event22nd Americas Conference on Information Systems: Surfing the IT Innovation Wave, AMCIS 2016 - San Diego, United States
Duration: Aug 11 2016Aug 14 2016

Other

Other22nd Americas Conference on Information Systems: Surfing the IT Innovation Wave, AMCIS 2016
CountryUnited States
CitySan Diego
Period8/11/168/14/16

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Computer Networks and Communications
  • Information Systems

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    Wong, M. Y., Zhou, Y., & Xu, H. (2016). Big data in fashion industry: Color cycle mining from runway data. In AMCIS 2016: Surfing the IT Innovation Wave - 22nd Americas Conference on Information Systems Association for Information Systems.