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Political Satire and the Decline of Discourse Quality: Evidence from China’s Online Public Sphere

Published online by Cambridge University Press:  30 March 2026

Xiaotong Chen
Affiliation:
School of Journalism and Communication, Tsinghua University, Beijing, China
Tianru Guan*
Affiliation:
School of Journalism and Communication, Wuhan University, Wuhan, China
*
Corresponding author: Tianru Guan; Email: guantianru@hotmail.com
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Abstract

Extensive research has examined whether political satire promotes or suppresses political discussion, but far less attention has been paid to how it shapes discourse quality. This study investigates the impact of political satire on discourse quality by scrutinizing the substance of online discussions in a non-democratic context. Drawing on manual content analysis of discussions on a major Chinese social media platform surrounding China’s controversial policy to raise the age of retirement, we analysed original posts and subsequent replies (N = 3,400) to assess the impact of satire on online political talk. The results show that political satire significantly decreases topic relevance and rationality, while exerting no significant effect on civility, and virtually precludes argument reciprocity. These findings contribute theoretically by shifting the focus from whether satire stimulates political engagement to how it influences the substantive quality of deliberation. They also invite a reassessment of the often-overemphasized optimistic role of political satire, highlighting its potential to erode rational and constructive discourse.

摘要

摘要

既有大量研究探讨了政治讽刺究竟是促进还是抑制了政治讨论, 但鲜有学者关注它如何塑造话语质量。本研究通过审视中国语境下网络讨论的实质内容, 考察了政治讽刺对话语质量的影响。基于对中国主流社交媒体平台上对“延迟退休”政策讨论的手动编码内容分析, 本研究分析了知乎平台上的原创帖文及其后续回复 (N =  3,400), 以评估讽刺在网络政治讨论中的作用。研究结果显示, 政治讽刺显著降低了话题相关性和理性程度, 对文明程度无显著影响, 且几乎完全阻断了观点的互惠互动。这些发现实现了理论视角的转换, 即从关注讽刺是否刺激政治参与, 转向关注其如何影响协商的实质质量。本研究也呼吁学界重新评估政治讽刺常被过度强调的积极作用, 警惕其侵蚀理性和建设性话语的潜在风险。

Information

Type
Research Article
Copyright
© The Author(s), 2026. Published by Cambridge University Press on behalf of SOAS University of London.
Figure 0

Table 1. Proportions of Each Independent Indicator to Describe DQITable 1 long description.

Figure 1

Table 2. Multilevel Logistic Regression Results (Robust Bayesian Estimation)Table 2 long description.

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