Abstract
The definition of “on-line hate speech” covers all forms of expression that propagate, incite, promote or justify hatred based on intolerance, including that expressed in the form of discrimination and hostility against minorities. Moreover, the concept of hatred includes other sub-concepts such as Homophobia, Racism, Chauvinism, Terrorism, Nationalism, Tolerance/Intolerance, and so on. Specifically, on-line hate speech is used in cases of cyber-harassment, to harm others deliberately, repeatedly and aggressively, in a way so to weaken victims psychologically. To contrast this phenomenon, EC has allocated a relevant amount of H2020 funds for the completion of specific research projects, the goal of which is the construction of computer tools to locate, evaluate and eventually block on-line hate speech. Today, the automatic tackling of online hatred is a daily-performed operation on Social Forums like Facebook, Twitter and Instagram. However, the algorithms these Social Forums use are stochastic/statistical, therefore not suitable to contextualize syntactically and semantically the words used inside posts. Therefore, with on-line hate speech tackling, statistical algorithms may produce inaccurate or even false results, with rather serious consequences.
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Notes
- 1.
Because of the complexity of the subject, it is not advisable to propose here an exhaustive analysis of the Italian negation grammar, which basically is also a subject well exposed in the literature and on the Web. However, it is important to stress here that Italian is a multiple-negation language: in sentences, propositions and expressions, the presence of two negative elements is not interpreted as a double denial equivalent to an affirmation of truth, as it is in Logic. This means that to evaluate hate speech in Italian, the analysis of declarative sentences may be not sufficient, and that the formalization of the negation grammar will be mandatory.
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Monteleone, M. (2019). NooJ Grammars and Ethical Algorithms: Tackling On-Line Hate Speech. In: Mirto, I., Monteleone, M., Silberztein, M. (eds) Formalizing Natural Languages with NooJ 2018 and Its Natural Language Processing Applications. NooJ 2018. Communications in Computer and Information Science, vol 987. Springer, Cham. https://doi.org/10.1007/978-3-030-10868-7_16
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