Abstract: In this paper we present an approach to develop a text-classification model which would be able to identify populist content in text. The developed BERT-based model is largely successful in identifying populist content in text and produces only a negligible amount of False Negatives, which makes it well-suited as a content analysis automation tool, which shortlists potentially relevant content for human validation.

翻译：摘要:在本文件中,我们提出一种方法,以开发一种文本分类模式,能够识别文本中的民粹主义内容;基于BERT的发达模型基本上成功地在文本中识别了民粹主义内容,只产生了微不足道的数量的虚假负值,这使得它完全适合作为内容分析自动化工具,该工具为人类验证列出了可能相关的内容。