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A War of (Mis)Information: The Political Effects of Rumors and Rumor Rebuttals in an Authoritarian Country

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  • Huang, Haifeng

Abstract

Despite the prevalence of anti-government rumors in authoritarian countries, little is currently known about their effects on citizens’ attitudes toward the government, and whether the authorities can effectively combat rumors. With an experimental procedure embedded in two surveys about Chinese internet users’ information exposure, this study finds that rumors decrease citizens’ trust in the government and support of the regime. Moreover, individuals from diverse socio-economic and political backgrounds are similarly susceptible to thinly evidenced rumors. Rebuttals generally reduce people’s belief in the specific content of rumors, but often do not recover political trust unless the government brings forth solid and vivid evidence to back its refutation or win the endorsement of public figures broadly perceived to be independent. But because such high-quality and strong rebuttals are hard to come by, rumors will erode political support in an authoritarian state. These findings have rich implications for studies of rumors and misinformation in general, and authoritarian information politics in particular.

Suggested Citation

  • Huang, Haifeng, 2017. "A War of (Mis)Information: The Political Effects of Rumors and Rumor Rebuttals in an Authoritarian Country," British Journal of Political Science, Cambridge University Press, vol. 47(2), pages 283-311, April.
  • Handle: RePEc:cup:bjposi:v:47:y:2017:i:02:p:283-311_00
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    Cited by:

    1. Jyoti Prakash Singh & Abhinav Kumar & Nripendra P. Rana & Yogesh K. Dwivedi, 2022. "Attention-Based LSTM Network for Rumor Veracity Estimation of Tweets," Information Systems Frontiers, Springer, vol. 24(2), pages 459-474, April.
    2. Greg Chih-Hsin Sheen & Hans H. Tung & Chien-Huei Wu & Wen-Chin Wu, 2023. "WHO approves? Relative trust, the WHO, and China’s COVID-19 vaccines," The Review of International Organizations, Springer, vol. 18(3), pages 499-521, July.
    3. Lu, Peng & Deng, Liping & Liao, Hongbing, 2019. "Conditional effects of individual judgment heterogeneity in information dissemination," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 335-344.
    4. Bernd Schlipphak & Mujtaba Isani & Mitja D. Back, 2022. "Conspiracy Theory Beliefs and Political Trust: The Moderating Role of Political Communication," Politics and Governance, Cogitatio Press, vol. 10(4), pages 157-167.
    5. Huo, Liang’an & Ma, Chenyang, 2017. "The interaction evolution model of mass incidents with delay in a social network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 484(C), pages 440-452.
    6. Alzahrani, Ahmed Ibrahim & Sarsam, Samer Muthana & Al-Samarraie, Hosam & Alblehai, Fahad, 2023. "Exploring the sentimental features of rumor messages and investors' intentions to invest," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 433-444.
    7. Lu, Peng & Yao, Qi & Lu, Pengfei, 2019. "Two-stage predictions of evolutionary dynamics during the rumor dissemination," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 349-369.
    8. Seoyong Kim & Sunhee Kim, 2020. "The Crisis of Public Health and Infodemic: Analyzing Belief Structure of Fake News about COVID-19 Pandemic," Sustainability, MDPI, vol. 12(23), pages 1-23, November.
    9. Lu, Peng & Nie, Shizhao, 2019. "The strength distribution and combined duration prediction of online collective actions: Big data analysis and BP neural networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    10. Lu, Peng, 2019. "Heterogeneity, judgment, and social trust of agents in rumor spreading," Applied Mathematics and Computation, Elsevier, vol. 350(C), pages 447-461.

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