License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/OASIcs.LDK.2021.13
URN: urn:nbn:de:0030-drops-145493
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Jokić, Danka ; Stanković, Ranka ; Krstev, Cvetana ; Šandrih, Branislava

A Twitter Corpus and Lexicon for Abusive Speech Detection in Serbian

OASIcs-LDK-2021-13.pdf (1 MB)


Abusive speech in social media, including profanities, derogatory and hate speech, has reached the level of a pandemic. A system that would be able to detect such texts could help in making the Internet and social media a better and more respectful virtual space. Research and commercial application in this area were so far focused mainly on the English language. This paper presents the work on building AbCoSER, the first corpus of abusive speech in Serbian. The corpus consists of 6,436 manually annotated tweets, out of which 1,416 were labelled as tweets using some kind of abusive speech. Those 1,416 tweets were further sub-classified, for instance to those using vulgar, hate speech, derogatory language, etc. In this paper, we explain the process of data acquisition, annotation, and corpus construction. We also discuss the results of an initial analysis of the annotation quality. Finally, we present an abusive speech lexicon structure and its enrichment with abusive triggers extracted from the AbCoSER dataset.

BibTeX - Entry

  author =	{Joki\'{c}, Danka and Stankovi\'{c}, Ranka and Krstev, Cvetana and \v{S}andrih, Branislava},
  title =	{{A Twitter Corpus and Lexicon for Abusive Speech Detection in Serbian}},
  booktitle =	{3rd Conference on Language, Data and Knowledge (LDK 2021)},
  pages =	{13:1--13:17},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-199-3},
  ISSN =	{2190-6807},
  year =	{2021},
  volume =	{93},
  editor =	{Gromann, Dagmar and S\'{e}rasset, Gilles and Declerck, Thierry and McCrae, John P. and Gracia, Jorge and Bosque-Gil, Julia and Bobillo, Fernando and Heinisch, Barbara},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{},
  URN =		{urn:nbn:de:0030-drops-145493},
  doi =		{10.4230/OASIcs.LDK.2021.13},
  annote =	{Keywords: abusive language, hate speech, Serbian, Twitter, lexicon, corpus}

Keywords: abusive language, hate speech, Serbian, Twitter, lexicon, corpus
Collection: 3rd Conference on Language, Data and Knowledge (LDK 2021)
Issue Date: 2021
Date of publication: 30.08.2021

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