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Toxic Comment Classification For French Online Comments

机译:法国在线评论的毒性评论分类

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In this paper, we propose a supervised approach for toxic comment classification for French language. We choose a set of features proposed for toxic comment detection for English and use it for French toxic comment detection. Our approach is based on N-gram features, linguistic features and a dictionary of insulting words and expressions. We obtain a F1-score of 78% with N-grams, linguistic and lexicon features, a precision of 87% with N-gram features and a recall of 83% with N-gram, linguistic and lexicon features. Classifier used are linear SVM and decision tree.
机译:在本文中,我们向法语提出了一种受到毒性评论分类的监督方法。我们为英语选择了一组针对毒性评论检测的功能,并使用它进行法式毒性评论检测。我们的方法是基于N-GRAM功能,语言特征和侮辱性词语的字典。我们获得了N-Grams,语言和词典特征的F1分数为78%,具有87%的精度,N-Gram功能,召回为83%,N-Gram,语言和词典功能。使用的分类器是线性SVM和决策树。

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