Hate Speech Annotation: Analysis of an Italian Twitter Corpus
Authors: Fabio Poletto, Marco Stranisci, Manuela Sanguinetti, Viviana Patti, Cristina Bosco (Università di Torino, ACMOS, 2017)
Topic: Sentiment, Emotion, Irony, Hate

Abstract
The paper describes the development of a corpus from social media built with the aim of representing and analysing hate speech against some minority groups in Italy. The issues related to data collection and annotation are introduced, focusing on the challenges we addressed in designing a multifaceted set of labels where the main features of verbal hate expressions may be modelled. Moreover, an analysis of the disagreement among the annotators is presented in order to carry out a preliminary evaluation of the data set and the scheme.

Introduction
Hate is all but a new phenomenon, yet the global spread of Internet and social network services has provided it with new means and forms of dissemination. Online hateful content, or Hate Speech (HS), is characterised by some key aspects (such as virality, or presumed anonymity) which distinguish it from offline communication and make it potentially more dangerous and hurtful AUTHOR. % namely: virality, permanence, presumed anonymity, distance from the target. These traits make online HS potentially more dangerous and hurtful than its "traditional" counterpart. What is more, HS is featured as a complex and multifaceted phenomenon, also because of the variety of approaches employed in attempting to draw the line between HS and free speech AUTHOR. Therefore, despite the multiple efforts, there is yet no universally accepted definition of HS.\% Therefore when discussing about HS, several scholars start with saying that despite the multiple efforts there is yet no universally accepted definition of it.\\ From a juridical perspective, two contrasting approaches can be recognised: while US law is oriented, quite uniquely, towards granting freedom of speech above all, even when potentially hurtful or threatening, legislation in Europe and the rest of the world tends to protect the dignity and rights of minority groups against any form of expression that might violate or endanger them.\\ Several European treaties and conventions ban HS: to mention but one, the Council of European Union condemns publicly inciting violence or hatred towards persons or groups defined by reference to race, colour, religion, descent or national or ethnic origin. The No Hate Speech Movement}, promoted by the Council of Europe, is also worth-mentioning for its efforts in endorsing responsible behaviours and preventing HS among European citizens.\\ The main aim of this paper is at introducing a novel resource which can be useful for the investigation of HS in a sentiment analysis perspective AUTHOR. Providing that among the minority groups targeted by HS, the present socio-political context shows that some of them are especially vulnerable and garner constant attention - often negative - from the public opinion, i.e. immigrants AUTHOR, Roma and Muslims, we decided to focus our work on HS against such groups. % one is especially vulnerable and garners constant attention - often negative - from the public opinion, i.e. immigrants, we decided to work mainly on HS against immigrants. Nevertheless, considering that an operational definition of HS may be better extracted from data where a larger set of targets are considered and compared, we collected data where also other HS targets occur. Furthermore, providing the spread of HS in social media together with their current relevance in communication, we focused on texts from Twitter, whose peculiar structure and conventions make it particularly suitable for data gathering and analysis.

Conclusion
We introduced in this paper the collection and annotation of an Italian Twitter corpus representing HS towards some selected target. Our main aim is at producing a corpus to be used for training and testing sentiment analysis systems, but some effort must still be applied to achieve this goal. The current contribute is mainly in designing and trying a novel schema for HS, but the relatively low agreement shows that modelling this phenomenon is a very challenging task and a further refinement of the guidelines and of the scheme must be applied, together with the application to larger data sets.