Information Channel Matters for Coordination During COVID-19 Pandemic: Evidence from Foreigners in China

Jie Chen, Wendao Liu


Based on an online questionnaire survey that focusing on foreigners in China conducted between the end of March and early April of 2020, this work finds that the language is a major obstacle that preventing foreigners living in China to get same consciousness of COVID-19 pandemic as local Chinese. It also shows the difference in information source significantly affect foreigners’ information accessibility as well as attitudes towards the pandemic. We call for more efforts to eliminate the language barriers in the transmission of pandemic information, which can be critical for global coordination in the current fight against the COVID-19 pandemic.


COVID-19, pandemic, language barrier, global coordination

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Calisher, C. et al. (2020) ‘Statement in support of the scientists, public health professionals, and medical professionals of China combatting COVID-19’, The Lancet, 395(10226), pp. e42–e43. doi: 10.1016/S0140-6736(20)30418-9.

Castillo, C., Mendoza, M. and Poblete, B. (2011) ‘Information credibility on twitter’, in Proceedings of the 20th international conference on World wide web - WWW ’11. New York, New York, USA: ACM Press, p. 675. doi: 10.1145/1963405.1963500.

Chen, J. and Liu, W. (2020) The impacts of COVID-19 on Foreigners Living in China: Evidence from An Online Survey. Shanghai. Available at:

Depoux, A. et al. (2020) ‘The pandemic of social media panic travels faster than the COVID-19 outbreak’, Journal of Travel Medicine. doi: 10.1093/jtm/taaa031.

Flanagin, A. J. and Metzger, M. J. (2000) ‘Perceptions of Internet Information Credibility’, Journalism & Mass Communication Quarterly, 77(3), pp. 515–540. doi: 10.1177/107769900007700304.

Ienca, M. and Vayena, E. (2020) ‘On the responsible use of digital data to tackle the COVID-19 pandemic’, Nature Medicine, 26(4), pp. 463–464. doi: 10.1038/s41591-020-0832-5.

Larson, H. J. (2020) ‘Blocking information on COVID-19 can fuel the spread of misinformation’, Nature, 580(7803), pp. 306–306. doi: 10.1038/d41586-020-00920-w.

OECD (2020) AI-powered COVID-19 watch, The Website of OECD. Available at: (Accessed: 30 April 2020).

Pulido, C. M. et al. (2020) ‘COVID-19 infodemic: More retweets for science-based information on coronavirus than for false information’, International Sociology, p. 026858092091475. doi: 10.1177/0268580920914755.

Pulido Rodríguez, C. et al. (2020) ‘False news around COVID-19 circulated less on Sina Weibo than on Twitter. How to overcome false information?’, International and Multidisciplinary Journal of Social Sciences, p. 1. doi: 10.17583/rimcis.2020.5386.

The Lancet (2020) ‘COVID-19: fighting panic with information’, The Lancet, 395(10224), p. 537. doi: 10.1016/S0140-6736(20)30379-2.

WHO (2020) WHO Collection for Coronavirus disease (COVID-19) outbreak, WHO Website. Genvea. Available at: (Accessed: 27 April 2020).

Zarocostas, J. (2020) ‘How to fight an infodemic’, The Lancet, 395(10225), p. 676. doi: 10.1016/S0140-6736(20)30461-X.



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Chinese Public Administration Review (ISSN 1539-6754, Online ISSN 2573-1483)  is published by the School of Government, Sun Yat-sen University.