Proceedings of the First Workshop on Abusive Language Online 2017
DOI: 10.18653/v1/w17-3007
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Legal Framework, Dataset and Annotation Schema for Socially Unacceptable Online Discourse Practices in Slovene

Abstract: In this paper we present the legal framework, dataset and annotation schema of socially unacceptable discourse practices on social networking platforms in Slovenia. On this basis we aim to train an automatic identification and classification system with which we wish contribute towards an improved methodology, understanding and treatment of such practices in the contemporary, increasingly multicultural information society.

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Cited by 67 publications
(52 citation statements)
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“…For annotating the datasets, we used a two-dimensional annotation schema an early version of which was presented in [2], covering both the type of potentially socially unacceptable discourse and the target this discourse is aimed at. The annotation was performed in PyBossa, 23 a web-based crowdsourcing tool.…”
Section: Dataset Annotationmentioning
confidence: 99%
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“…For annotating the datasets, we used a two-dimensional annotation schema an early version of which was presented in [2], covering both the type of potentially socially unacceptable discourse and the target this discourse is aimed at. The annotation was performed in PyBossa, 23 a web-based crowdsourcing tool.…”
Section: Dataset Annotationmentioning
confidence: 99%
“…The annotation schemas used in these datasets are very different, ranging from encoding multiple toxicity levels, covert vs. overt aggressiveness, the target of the inappropriateness only etc. The first two pieces of work to take into account both the type of SUD and its target are the annotation schema presented in [2] (which is used in the dataset presented in this paper) and the OLID dataset [9].…”
Section: Introductionmentioning
confidence: 99%
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“…They have used two classes: Hate and Non-hate. [16] proposed hate speech classification task Slovene language at SN Computer Science multiple granularities. At a coarse level, they have identified two classes SUD (Socially Unacceptable Online Discourse), and not SUD.…”
Section: State Of the Artmentioning
confidence: 99%
“…Mubarak et al (2017) addresses abusive language detection on Arabic social media and Su et al (2017) presents a system to detect and rephrase profanity in Chinese. Hate speech and abusive language datasets have been recently annotated for German (Ross et al, 2016) and Slovene (Fišer et al, 2017) opening avenues for future work in languages other than English.…”
Section: Introductionmentioning
confidence: 99%