We consider a particular hate speech corpus -a Twitter corpus collected by <cite>Waseem and Hovy (2016)</cite> , which has been gaining traction as a resource for training hate speech detection models<cite> (Waseem and Hovy, 2016</cite>; Gambäck and Utpal, 2017; Park and Fung, 2017) -and analyse it critically to better understand its usefulness as a hate speech resource.