Although there is an unprecedented effort to provide adequate responses in terms of laws and policies to hate content on social media platforms, dealing with hatred online is still a tough problem. Tackling hate speech in the standard way of content deletion or user suspension may be charged with censorship and overblocking. One alternate strategy, that has received little attention so far by the research community, is to actually oppose hate content with counter-narratives (i.e. informed textual responses). In this paper, we describe the creation of the first large-scale, multilingual, expert-based dataset of hate speech/counter-narrative pairs. This dataset has been built with the effort of more than 100 operators from three different NGOs that applied their training and expertise to the task. Together with the collected data we also provide additional annotations about expert demographics, hate and response type, and data augmentation through translation and paraphrasing. Finally, we provide initial experiments to assess the quality of our data.

CONAN - COunter NArratives through Nichesourcing: a Multilingual Dataset of Responses to Fight Online Hate Speech / Chung, Yl; Kuzmenko, E; Tekiroglu, Ss; Guerini, M. - ELETTRONICO. - (2019), pp. 2819-2829. ((Intervento presentato al convegno Annual Meeting of the Association for Computational Linguistics tenutosi a Firenze nel 28th July-2nd August 2019.

CONAN - COunter NArratives through Nichesourcing: a Multilingual Dataset of Responses to Fight Online Hate Speech

Tekiroglu, SS;Guerini, M
2019

Abstract

Although there is an unprecedented effort to provide adequate responses in terms of laws and policies to hate content on social media platforms, dealing with hatred online is still a tough problem. Tackling hate speech in the standard way of content deletion or user suspension may be charged with censorship and overblocking. One alternate strategy, that has received little attention so far by the research community, is to actually oppose hate content with counter-narratives (i.e. informed textual responses). In this paper, we describe the creation of the first large-scale, multilingual, expert-based dataset of hate speech/counter-narrative pairs. This dataset has been built with the effort of more than 100 operators from three different NGOs that applied their training and expertise to the task. Together with the collected data we also provide additional annotations about expert demographics, hate and response type, and data augmentation through translation and paraphrasing. Finally, we provide initial experiments to assess the quality of our data.
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
209 N EIGHTH STREET, STROUDSBURG, PA 18360 USA
ASSOC COMPUTATIONAL LINGUISTICS-ACL
Chung, Yl; Kuzmenko, E; Tekiroglu, Ss; Guerini, M
CONAN - COunter NArratives through Nichesourcing: a Multilingual Dataset of Responses to Fight Online Hate Speech / Chung, Yl; Kuzmenko, E; Tekiroglu, Ss; Guerini, M. - ELETTRONICO. - (2019), pp. 2819-2829. ((Intervento presentato al convegno Annual Meeting of the Association for Computational Linguistics tenutosi a Firenze nel 28th July-2nd August 2019.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11572/258065
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