NooJ Grammars and Ethical Algorithms: Tackling On-Line Hate Speech
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.
KeywordsNooJ NooJ finite-state automata/transducers On-line hate speech Ethical algorithms Rule-based algorithms Statistical algorithms
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