Detecting Online Counterfeit-goods Seller using Connection Discovery

Abstract

With the advancement of social media and mobile technology, any smartphone user can easily become a seller on social media and e-commerce platforms, such as Instagram and Carousell in Hong Kong or Taobao in China. A seller shows images of their products and annotates their images with suitable tags that can be searched easily by others. Those images could be taken by the seller, or the seller could use images shared by other sellers. Among sellers, some sell counterfeit goods, and these sellers may use disguising tags and language, which make detecting them a difficult task. This article proposes a framework to detect counterfeit sellers by using deep learning to discover connections among sellers from their shared images. Based on 473K shared images from Taobao, Instagram, and Carousell, it is proven that the proposed framework can detect counterfeit sellers. The framework is 30% better than approaches using object recognition in detecting counterfeit sellers. To the best of our knowledge, this is the first work to detect online counterfeit sellers from their shared images.