Decoding political trust in China : a machine learning analysis

Lianjiang LI*

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)peer-review

10 Citations (Scopus)


Survey results inflate political trust in China if the observed trust in the central government is mistaken for the latent trust in the Centre. The target of trust in the country is the Centre, which is ultimately the top leader. The critical issue domain for assessing the Centre's trustworthiness is policy implementation rather than policymaking. The Centre's trustworthiness has two dimensions: commitment to good governance and the capacity to discipline local officials. Observed trust in the central government indicates trust in the Centre's commitment, while observed trust in the local government reflects confidence in the Centre's capacity. A machine learning analysis of a national survey reveals how much conventional reading overestimates political trust. At first glance, 85 per cent of the respondents trust the central government. Upon further inspection, 18 per cent have total trust in the Centre, 34 per cent have partial trust and 33 per cent are sceptical.


Original languageEnglish
Pages (from-to)1-20
Number of pages20
JournalChina Quarterly
Publication statusPublished - Mar 2022
Externally publishedYes

Bibliographical note

Publisher Copyright:
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of SOAS University of London.


  • China
  • machine learning
  • political trust
  • trust in the central government
  • trust in the Centre
  • trust in the local government
  • 政治信任
  • 对中央的信任
  • 对中央政府的信任
  • 对地方政府的信任
  • 机器学习
  • 中国


Dive into the research topics of 'Decoding political trust in China : a machine learning analysis'. Together they form a unique fingerprint.

Cite this