Social4Fashion: An intelligent expert system for forecasting fashion trends from social media contents

Abstract

The fashion field is continually expanding and evolving, and social media play a significant role in shaping current fashion trends through the influence of online personalities, such as influencers. As a result, fashion designers often turn to social media to gain insights into the latest trends and draw inspiration, while in the past they used to physically visit fashion districts. To automate and speed up this process, an expert system is much needed; thus, Social4Fashion has been created, an end-to-end framework that leverages deep learning-based techniques in order to support creatives in their research and decision-making process, with the final goal of analyzing and predicting trends. This system employs several steps, starting with the automatic data collection from Instagram, using hashtags provided by domain experts. Next, retrieved images are filtered to remove non-fashion related pictures, leaving only those pertaining to the fashion area for further processing. Then, to obtain more specific information about the images, the handbags present (if any) are detected and classified, based on their type; finally, dominant colors of the handbags are retrieved through clustering on the images. All the data collected with this system are then stored and analyzed via user-friendly dashboards, created with the objective of highlighting relevant information, in order to perform analysis on current and future fashion trends. Results show the effectiveness of the proposed system, with an accuracy of 97% (95% confidence interval 0.95–1) for the fashion image classification and a mAP of 0.77 (95% confidence interval 0.73–0.82) for the handbag detection, which makes it suitable for fashion domain analysis. Also, as a result of this work, a novel fashion-related dataset has been made available to the research community. This system can greatly improve the way fashion trends are analyzed, and allow for more efficient and effective design processes in the future.