用户讨厌金发女郎:检测性别歧视的用户评论在线罗马尼亚新闻

Andreea-Loredana Moldovan, Karla-Claudia Csürös, Ana-Maria Bucur, Loredana Bercuci
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引用次数: 1

摘要

在政治代表性别平等方面,罗马尼亚在欧洲排名垫底,女性参政人数比欧盟平均水平低10%。我们的假设是,这种代表性不足也受到女性政治家在公共领域,特别是在网络媒体中面临的性别歧视和言语虐待的影响。我们从报纸上关于罗马尼亚女政治家的文章中收集了一个新的数据集,其中包含罗马尼亚语的性别歧视评论,并使用经典的机器学习模型和微调的预训练变压器模型提出基线模型,用于在线媒体中性别歧视语言的分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Users Hate Blondes: Detecting Sexism in User Comments on Online Romanian News
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 collect a novel dataset with sexist comments in Romanian language from newspaper articles about Romanian female politicians and propose baseline models using classical machine learning models and fine-tuned pretrained transformer models for the classification of sexist language in the online medium.
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