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        'level-of-annotation': ['Tweets'],
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        reference: 'Caselli, T., Basile, V., Jelena, M., Inga, K., and Michael, G. 2020. "I feel offended, don’t be abusive! implicit/explicit messages in offensive and abusive language". The 12th Language Resources and Evaluation Conference (pp. 6193-6202). European Language Resources Association.'
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      url_path: 'dataset-2',
      file_path: 'content/dataset-2/index.md',
      metadata: {
        title: 'Abusive Language Detection on Arabic Social Media (Al Jazeera)',
        'link-to-publication': 'https://www.aclweb.org/anthology/W17-3008',
        'link-to-data': 'http://alt.qcri.org/~hmubarak/offensive/AJCommentsClassification-CF.xlsx',
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        platform: ['AlJazeera'],
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      metadata: {
        title: 'CoRAL: a Context-aware Croatian Abusive Language Dataset',
        'link-to-publication': 'https://aclanthology.org/2022.findings-aacl.21/',
        'link-to-data': 'https://github.com/shekharRavi/CoRAL-dataset-Findings-of-the-ACL-AACL-IJCNLP-2022',
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        'details-of-task': 'Detectioning CDC from abusive comments',
        'size-of-dataset': 2240,
        'percentage-abusive': 100,
        language: 'Croatian',
        'level-of-annotation': ['Posts'],
        platform: ['Posts'],
        medium: ['Newspaper Comments'],
        reference: 'Ravi Shekhar, Mladen Karan and Matthew Purver (2022). CoRAL: a Context-aware Croatian Abusive Language Dataset. Findings of the ACL: AACL-IJCNLP.'
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      metadata: {
        title: 'Detecting Abusive Albanian',
        'link-to-publication': 'https://arxiv.org/abs/2107.13592',
        'link-to-data': 'https://doi.org/10.6084/m9.figshare.19333298.v1',
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