Abstract
Due to an exponential increase in the use of Internet by persons from different countries and educational backgrounds, the offensive online language detection has become a significant task facing natural language processing. Considering the major negative impact of this type of content in the case of youngers, detecting online toxic language to protect users’ online safety becomes an urgent issue. The project has two main goals: (1) developing an annotated corpus of offensive content for Romanian language and (2) testing various machine learning algorithms to identify a best approach. The proposed methods achieve results with a few percentages more than the accuracy of the current SoTA.
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