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September 2, 2026Journalism Studies

News is Becoming Similar? A Diachronic Text Mining Exploration of News Convergence in Chinese Media

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Authors

JQJunheng QianZZZhi-Jin Zhong

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Overview

Computational text analysis reveals rising lexical convergence in global Chinese reporting alongside opposing audience engagement trends, highlighting context-dependent media dynamics.

Key Points

  • To quantify temporal patterns of lexical and thematic news convergence in Chinese media across domestic and global settings and assess their influence on audience engagement.
  • Analyzed N = 607,871 news posts from four prominent Chinese media outlets published over a 10-year period.
  • Applied diachronic computational text-mining algorithms to track changes in lexical similarity and thematic structural similarity over time.
  • Evaluated associations between textual convergence metrics and audience engagement metrics across domestic and international reporting contexts.
  • Lexical similarity demonstrated a significant upward trend across Chinese media in the global reporting context, but showed no increase in the domestic context.
  • Thematic structural similarity showed no significant upward trend over time in either domestic or global media contexts.
  • Higher lexical similarity correlated negatively with audience engagement in the domestic context, whereas both lexical and thematic similarity correlated positively with audience engagement in the global context.

Cite This Study

Qian et al. (2026) studied this question.

synapsesocial.com/papers/6a97e2eac562ede874ec744fhttps://doi.org/10.1080/1461670x.2026.2719575
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