Detecting Misogyny and Xenophobia in Spanish Tweets Using Language Technologies

Abstract

Today, misogyny and xenophobia are some of the most important social problems. With the increase in the use of social media, this feeling of hatred toward women and immigrants can be more easily expressed, and therefore it can have harmful effects on social media users. For this reason, it is important to develop systems capable of detecting hateful comments automatically. In this article, we analyze the hate speech in Spanish tweets against women and immigrants conducting classification experiments using different approaches. Moreover, we create appropriate language resources for hate speech detection in Spanish.