Romania ranks almost last in Europe when it comes to gender equality in political representation, with about 10% fewer women in politics than the E.U. average. We proceed from the assumption that this underrepresentation is also influenced by the sexism and verbal abuse female politicians face in the public sphere, especially in online media. We propose a novel dataset with sexist comments in Romanian language from online newspaper articles about Romanian female politicians and experiment with baseline models using classical machine learning models and fine-tuned pre-trained transformer models for the classification of sexist language in the online medium.
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