Invited talk at University of Florence

The widespread use of social media yields a huge number of interactions on the Web. Unfortunately, social media messages are often written to attack specific groups of users based on their religion, ethnicity or social status. Due to the massive rise of hateful, abusive, offensive messages, platforms such as Twitter and Facebook have been searching for solutions to tackle hate speech. As a consequence, the amount of research targeting the detection of hate speech, abusive language and cyberbullying also shows an increase. In this talk we will present two projects in the field of hate speech analysis and detection: CREEP which aims at identifying and preventing the possible negative impacts of cyberbullying on young people and HateMeter, whose goal is to increase the efficiency and effectiveness of NGOs in preventing and tackling Islamophobia at EU level. In particular, we will describe the language resources and technologies under development in the two projects and we will show two demos based on Natural Language Processing tools.