Universitat Politècnica de València, Spain
Stance and Misogyny: Analysing Cases of Hate Speech
Abstract. Once upon a time we believed in the wisdom of crowds and that we could learn from what others discussed in social media. Nowadays, we are not so sure about it. Comments in social media often lack of aurgumentation and users do not try to persuade others to agree with their claim by presenting evidence. Communication is mostly with users belonging to the same community with the risk of an intellectual isolation (filter bubble), where beliefs may be reinforced by a repeated message inside the closed community (echo chamber). When users communicate with someone who disagrees with their viewpoints, they often do it spewing hateful comments behind a veil of anonymity. This may only increase political and social polarization and
extremism. In this keynote, we will show some cases of hate speech in Twitter we came across in the datasets of two shared tasks we organized at IberEval on stance detection and misogyny identification. We will also comment how some participants detect them.