Identifying Populist Paragraphs in Text: A machine-learning approach

TL;DR

This paper introduces a BERT-based machine learning model designed to automatically identify populist content in text, achieving high accuracy with minimal false negatives, thus aiding content analysis automation.

Contribution

The paper presents a novel BERT-based approach for populist content detection, demonstrating its effectiveness in automating content analysis with high precision.

Findings

High accuracy in identifying populist content

Negligible false negatives in detection

Effective as a content analysis automation tool

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.