Computational Linguistics Against Hate: Hate Speech Detection and Visualization on Social Media in the "Contro L’Odio" Project
Authors: Arthur T. E. Capozzi, Mirko Lai, Valerio Basile, Cataldo Musto, Marco Polignano, Fabio Poletto, Manuela Sanguinetti, Cristina Bosco, Viviana Patti, Giancarlo Ruffo, Giovanni Semeraro, Marco Stranisci (Università di Torino, Università di Bari Aldo Moro, ACMOS, 2019)
Topic: Sentiment, Emotion, Irony, Hate

Abstract
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 vast amount of information through interactive maps, also tuning their view, e.g., visualizing the most viral tweets and interactively reducing the inherent complexity of the data. Educational courses for high school students and citizens have been developed, centered on the platform, and focused on the deconstruction of negative stereotypes against immigrants, Roma, and religious minorities, as well as on the creation of positive narratives.

Introduction
Hate Speech (HS) is a multi-faceted phenomenon with countless nuances, a high degree of individual and cultural variation, and intersections with related concepts such as offensive language, threats, bullying, and so on. The detection of HS is a recent yet popular task that is gaining the attention of the NLP community but also that of public institutions and private companies. There are several problems connected with this delicate task: a cultural-dependent definition, a highly subjective perception, the need to remove potentially illegal contents quickly from the Web and the connected risk to unjustly remove legal content, the partly overlapping linguistic phenomena that make it hard to identify HS. English social media texts are the most studied, but other languages, sources, and textual genres are investigated as well. “Contro l’odio” is a project for countering and preventing racist discrimination and HS in Italy, in particular focused against immigrants. On the one hand, the project follows and extends the research outcomes emerged from the ‘Italian Hate Map project’ (Musto et al., 2016), whose goal was to identify the most-at-risk areas of the Italian country, that is to say, the areas where the users more frequently publish hate speech, by exploiting semantic analysis and opinion mining techniques. On the other hand, “Contro l’odio” benefits from the availability of annotated corpora for sentiment analysis, hate speech detection, and related phenomena such as aggressiveness and offensiveness, to be used for training and tuning the HS detection tools (Sanguinetti et al., 2018; Poletto et al., 2017). The project brings together the competences and active participation of civil society organizations Acmos and Vox, and two academic research groups, respectively from the University of Bari and Turin. This paper focuses on the technological core of the project, a Web platform that combines computational linguistics analysis with visualization techniques, in order to provide users with an interactive interface for exploring the dynamics of the discourse of hate against immigrants in Italian social media. Three typical targets of discrimination related to this topical focus are taken into account, namely Migrants, Muslims, and Roma, since they exemplify discrimination based on nationality, religious beliefs, and ethnicity, respectively. Since November 2018, the platform analyzes daily Twitter posts and exploits temporal and geo-spatial information related to messages in order to ease the summarization of the hate detection outcome.

Conclusion
In this paper we described an online platform for monitoring HS against immigrants in Italy at different levels of granularity, which uses Twitter as a data source and combines HS detection and advanced visualization techniques in order to provide users with an interactive interface for the exploration of the resulted data. Another important research outcome of the project is HATECHECKER, a tool that automatically detects hater users in online social networks, which will be accessible from the platform soon. Given a target user, the workflow that is going to be implemented in our system uses sentiment analysis techniques to identify hate speech posted by the user, and exploits a lexicon-based approach to assign to the person one or more labels that describe the nature of the hate speech she posted (e.g., racism, homophobia, sexism, etc.). A map of Italian projects and associations that spread a culture of tolerance is also under development, to allow ‘Contro l’Odio’ users to get a better understanding of the HS phenomenon and of the active forces fighting it on the Italian territory.