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Measuring Chinese online populist discourse: an automated semantic text analysis method

  • Yuzhou Tao
  • , Zhiqin Zhan
  • , Han Zhou
  • , Jingshi Kang
  • , Shaojing Sun*
  • *Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

2 Citations (Scopus)

Abstract

Based on conceptualizing Chinese online populism as a grassroots discourse and operationalizing it in terms of people-centrist and anti-elitist dimensions, we developed an automated semantic text analysis method for analyzing Chinese online populist discourse both quantitatively and qualitatively. First, we introduced semantic role labeling to reformulate the original text into semantic triplets. Second, we created a Chinese populism dictionary containing terms signifying “the people,” “elites,” and “popular sovereignty.” Third, we developed a rule-based method to recognize populist discourse automatically. The automated semantic text analysis method can capture a great deal of qualitative information throughout this process for further analysis. The validation test showed that the automated semantic text analysis method performed satisfactorily (accuracy > 0.9). This method not only creates a broadly applicable and reliable tool for studying Chinese online populism, but it also contributes to the literature on how populism manifests in various cultural and political contexts, expanding the possibilities of populism research globally.
Original languageEnglish
Pages (from-to)121-141
Number of pages21
JournalChinese Journal of Communication
Volume18
Issue number2
Early online date12 Nov 2024
DOIs
Publication statusPublished - 3 Apr 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 16 - Peace, Justice and Strong Institutions
    SDG 16 Peace, Justice and Strong Institutions

User-Defined Keywords

  • Chinese context
  • Online populism
  • Computational methods
  • Populist discourse
  • Semantic text analysis

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