Online Social Networks have become a cornerstone of Web 2.0 era. Internet users around the world use Online Social Networks as primary sources to consume news, updates, and information about events around the world. However, given the enormous volume and veracity, it is hard to manually moderate all content that is generated and shared on these networks. This phenomenon enables hostile entities to generate and promote various types of poor quality content (including but not limited to scams, fake news, false information, rumors, untrustworthy or unreliable information) and pollute the information stream for monetary gains, hinder user experience, or to compromise system reputation. We aim to address this challenge of automatically identifying poor quality content on Online Social Networks. We focus our work on Facebook, which is currently the biggest Online Social Network.