Identifying Populist Paragraphs in Text: A machine-learning approach
This provides a tool for automating content analysis in political or media studies, though it is incremental as it applies an existing method to a specific domain.
The researchers tackled the problem of identifying populist content in text by developing a BERT-based classification model, which achieved high accuracy with negligible false negatives, making it suitable for automating content analysis and shortlisting for human validation.
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.