English

Identifying Populist Paragraphs in Text: A machine-learning approach

Computation and Language 2021-06-11 v2

Abstract

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.

Keywords

Cite

@article{arxiv.2106.03161,
  title  = {Identifying Populist Paragraphs in Text: A machine-learning approach},
  author = {Jogilė Ulinskaitė and Lukas Pukelis},
  journal= {arXiv preprint arXiv:2106.03161},
  year   = {2021}
}

Comments

18 pages, 2 Figures, 3 Tables in main text, 2 tables in Annexes

R2 v1 2026-06-24T02:53:05.927Z