Trendfashion - A framework for the identification of fashion trends

Abstract

The fashion industry faces different challenges regarding accurate forecasts for future fashion products. The consumer demand is volatile and sales periods of fashion products are short due to production plants in Asia and target markets in Europe. Besides standard statistical approaches based on historical data and advanced methods such as the application of artificial neural networks or fuzzy logic, there are fashion experts, who use different information sources, e.g. fairs, social media, fashion websites, to predict design-trends as well as sales volumes. In this paper we follow this expert-driven approach by collecting data from fashion weblogs, news sites and fashion magazines, in order to identify actual and future designtrends. For this aim, we develop the TrendFashion Tool which collects data from these fashion sources and analyse them. On a higher level, this tool successfully separates fashion related posts from non-fashion related posts. And on a lower level, it identifies fashion related words and weights them according to an index.