HateChecker: A tool to automatically detect hater users in online social networks

In this paper we present HateChecker, a tool for the automatic detection of hater users in online social networks which has been developed within the activities of”Contro L’Odio” research project. In a nutshell, our tool implements a methodology based on three steps: (i) all the Tweets posted by a target user are gathered and processed. (ii) sentiment analysis techniques are exploited to automatically label intolerant Tweets as hate speeches. (iii) a lexicon is used to classify hate speeches against a set of specific categories that can describe the target user (e.g., racist, homophobic, antisemitic, etc.). Finally, the output of the tool, that is to say, a set of labels describing (if any) the intolerant traits of the target user, are shown through an interactive user interface and exposed through a REST web service for the integration in third-party applications. In the experimental evaluation we crawled and annotated a set of 200 Twitter profiles and we investigated to what extent our tool is able to correctly identify hater users. The results confirmed the validity of our methodology and paved the way for several future research directions

Computational linguistics against hate: Hate speech detection and visualization on social media in the "Contro L’Odio" project

The paper describes the Web platform built within the project “Contro l’odio”, for monitoring and contrasting discrimination and hate speech against immigrants in Italy. It applies a combination of computational linguistics techniques for hate speech detection and data visualization tools on data drawn from Twitter. It allows users to access a huge amount of information through interactive maps, also tuning their view, e.g., visualizing the most viral tweets and interactively reducing the inherent complexity of data. Educational courses for high school students and citizenship has been developed which are centered on the platform and focused on the deconstruction of negative stereotypes against immigrants, Roma, and religious minorities, and on the creation of positive narratives

Computational linguistics against hate: Hate speech detection and visualization on social media in the “Contro L’Odio” project

The paper describes the Web platform built within the project “Contro l’odio”, for monitoring and contrasting discrimination and hate speech against immigrants in Italy. It applies a combination of computational linguistics techniques for hate speech detection and data visualization tools on data drawn from Twitter. It allows users to access a huge amount of information through interactive maps, also tuning their view, e.g., visualizing the most viral tweets and interactively reducing the inherent complexity of data. Educational courses for high school students and citizenship has been developed which are centered on the platform and focused on the deconstruction of negative stereotypes against immigrants, Roma, and religious minorities, and on the creation of positive narratives