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Public attitudes towards dialects: Evidence from 31 Chinese provinces

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  • Tianxin Li
  • Xigang Ke
  • Jin Li

Abstract

Background: Dialect Attitude is conceptualized as an individual’s cognitive and affective evaluation of a dialect and its speakers. In the contemporary China, dialect is suffering from significant stigmatization, resulting in social inequalities, which hinder sustainable development. This study aims to reveal the Chinese public attitudes towards dialects, and clarify the potential determinants related to heterogeneous attitudes at a macro level. Methods: We combine the crawler technology and sentiment analysis to conduct a provincial cross-sectional study. We collect 1,650,480 microblogs about public attitudes towards dialects from Microblog across 31 specific Chinese provinces. Spatial regression models are utilized to clarify the influence of macro-level determinants on differences in public attitudes. Results: The present study reveals that: (1) The Chinese public generally holds positive attitudes towards dialects, with significant variation between provinces. (2) Political Resource (β = 0.076, SD = 0.036, P

Suggested Citation

  • Tianxin Li & Xigang Ke & Jin Li, 2023. "Public attitudes towards dialects: Evidence from 31 Chinese provinces," PLOS ONE, Public Library of Science, vol. 18(10), pages 1-21, October.
    • Handle: RePEc:plo:pone00:0292852
    DOI: 10.1371/journal.pone.0292852
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    References listed on IDEAS

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    1. Yingxia Xue & Honglei Liu, 2023. "Exploration of the Dynamic Evolution of Online Public Opinion towards Waste Classification in Shanghai," IJERPH, MDPI, vol. 20(2), pages 1-15, January.
    2. Richard Frankel & Jared Jennings & Joshua Lee, 2022. "Disclosure Sentiment: Machine Learning vs. Dictionary Methods," Management Science, INFORMS, vol. 68(7), pages 5514-5532, July.
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