The goal of the Web Spam Challenge series is to identify and compare Machine Learning (ML) methods for automatically labeling structured data represented as graphs. More precisely, we focus on the problem of labeling all nodes of a graph from a partial labeling of them. The application we study is Web Spam Detection, where we want to detect deliberate actions of deception aimed at the ranking functions used by search engines.