The E-Commerce Market for \"Lemons\": Identification and Analysis of Websites Selling Counterfeit Goods

We investigate the practice of websites selling counterfeit goods. We inspect web search results for 225 queries across 25 brands. We devise a binary classifier that predicts whether a given website is selling counterfeits by examining automatically extracted features such as WHOIS information, pricing and website content. We then apply the classifier to results collected between January and August 2014. We find that, overall, 32% of search results point to websites selling fakes. For 'complicit' search terms, such as \"replica rolex\", 39% of the search results point to fakes, compared to 20% for 'innocent' terms, such as \"hermes buy online\". Using a linear regression, we find that brands with a higher street price for fakes have higher incidence of counterfeits in search results, but that brands who take active countermeasures such as filing DMCA requests experience lower incidence of counterfeits in search results. Finally, we study how the incidence of counterfeits evolves over time, finding that the fraction of search results pointing to fakes remains remarkably stable.