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A problem with this diversity is that they often differ, among other things, in context, platform, sampling process, collection strategy, and labeling schema. There have been surveys on these datasets, but they compare the datasets only superficially. Therefore, we developed a bias and comparison framework for abusive language datasets for their in-depth analysis and to provide a comparison of five English and six Arabic datasets. 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