The passage from a read-only to a read-write Web gave people the possibility to freely interact, share and collaborate through social networks, online communities, blogs, wikis and other online collaborative media. The democracy of the Web is what made it so popular in the past decades but such a high degree of freedom of expression also gave birth to negative side effects – the so called ‘dark side’ of the Web. An example of this is trolling i.e. the exploitation of the anonymity of the Web to post inflammatory and outrageous messages directed to one specific person or community to provoke them into a desired emotional response. Online community masters usually warn users against trolls with messages such as DNFTT (Do Not Feed The Trolls) but so far this has not been enough to stop trolls trolling. The aim of this work is to use Sentic Computing, a new paradigm for the affective analysis of natural language text, to detect trolls and hence prevent web-users from being emotionally hurt by malicious posts.