Fashion Colour Predictions by Social Media
The model makes use of a database comprising millions of posts from Facebook and Weibo, two of the most popular social media sites in the Greater-China region. Posts in both English and Chinese are used in the model. Authentic fashion posts that relate to colour are identified through Natural Language Processing (NLP). The model also applies advanced machine-learning methods to improve the accuracy of fashion colour prediction.
The project studied the transmission pattern of fashion colour information in social media and generated equations based on posts from fashion brands, magazines, designers and key opinion leaders.
The model can be customised for different users, based on their market positions and production lag time. In other words, the tool can be modified to match appropriately each user’s particular features and needs.
Upgrading traditional experience-based decision-making with analysis of current big data and machine learning modeling techniques, this project has great potential to generate fashion trend estimations in terms of colour range, style, fitting, and may even function to help drive a form of “new retail”, both on- and off-line.
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