Incomplete translation as a conduit for fake news: A case of coronavirus-related news

Main Article Content

Narongdej Phanthaphoommee


While scholars from various fields have pioneered studies of fake news and its consequences, there is currently a scarcity of literature on fake news and translation. The present paper aims to investigate the phenomenon of fake news as a product of translation in the Thai context. Using a discourse analysis approach to translation studies to determine the textual profile of the translated text, the researcher examined Thai translations of international news about the COVID-19 pandemic that have been proven to be untrue. The findings reveal that there are six major characteristics of fake news translations at word-level, sentence-level, stance, style, visual manipulation, and text structure and presentation. Many of these features lend depth to the existing literature on fake news in general, but a number of minor characteristics are unique to translation; namely, foreign word insertion, citation of foreign names, reporting of foreign people’s opinions, translation of already-fake news, disclaimer of attribution at the paratextual level, display of the English source text, and pseudotranslation. These characteristics contribute to fake news in the Thai target texts, which is arguably a form of incomplete translation created as the translator attempts to summarize source news and create news that appears to be from other countries. To complement previous research on fake news detection with computerized systems, this paper returns to the basics in the hopes of shedding some light on the fundamental detection of fake news derived from translation, particularly for lay audiences.


Download data is not yet available.

Article Details

Research Articles


Aphiwongsophon, S. and Chongstitvatana, P. (2018). Detecting fake news with machine learning method. Paper presented at the 2018 15th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON). Chiang Rai, Thailand. July 18–21. [Online URL:] accessed on May 4, 2021.

Batchelor, K. (2018). Translation and Paratexts. London: Routledge.

Bielsa, E. and Bassnett, S. (2009). Translation in Global News. London: Routledge.

Del Vicario, M., Quattrociocchi, W., Scala, A. and Zollo, F. (2019). Polarization and fake news: Early warning of potential misinformation targets. ACM Transactions on the Web 13(2): 10. [Online URL:] accessed on January 12, 2021.

Egelhofer, J. L. and Lecheler, S. (2019). Fake news as a two-dimensional phenomenon: A framework and research agenda. Annals of the International Communication Association 43(2): 97–116. [Online URL:] accessed on May 4, 2021.

Fairclough, N. (1995). Critical discourse analysis: The critical study of language. London: Longman.

Gardner, R. (2004). Conversation Analysis. In A. Davies and C. Elder (Eds.), The Handbook of Applied Linguistics, pp. 262–284. Oxford: Blackwell Publishing Ltd.

Genette, G. (1997). Paratexts: Thresholds of Interpretation, translated by J. E. Lewin. Cambridge: Cambridge University Press.

Hartley, K. and Vu, M. K. (2020). Fighting fake news in the COVID-19 era: Policy insights from an equilibrium model. Policy Sciences 53: 735–758. [Online URL:] accessed on June 14, 2021.

Hatim, B. and Mason, I. (1990). Discourse and the Translator. London: Routledge.

Hua, J. and Shaw, R. (2020). Corona virus (Covid-19) “infodemic” and emerging issues through a data lens: The case of China. International Journal of Environmental Research and Public Health 17(7): 2309. [Online URL:] accessed on April 26, 2021.

Kang, J. H. (2007). Recontextualization of news discourse: A case study of translation of news discourse on North Korea. The Translator 13(2): 219–242. [Online URL:] accessed on August 7, 2021.

Kaniklidou, T. and House, J. (2018). Discourse and ideology in translated children’s literature: A comparative study. Perspectives 26(2): 232–245. [Online URL:] accessed on May 4, 2021.

Kress, G. and van Leeuwen, T. (1996). Reading Images: The Grammar of Visual Design. New York: Routledge.

Laato, S., Islam, A. K. M. N., Islam, M. N. and Whelan, E. (2020). What drives unverified information sharing and cyberchondria during the COVID-19 pandemic? European Journal of Information Systems 29(3): 288–305. [Online URL:] accessed on August 7, 2021.

Lefevere, A. (1992). Translation, Rewriting, and the Manipulation of Literary Fame. London: Routledge.

Li, H. O.-Y., Bailey, A., Huynh, D. and Chan, J. (2020). YouTube as a source of information on COVID-19: A pandemic of misinformation? BMJ Global Health 5(5): e002604. [Online URL:] accessed on August 7, 2021.

Machin, D. and Mayr, A. (2012). How to Do Critical Discourse Analysis: A Multimodal Introduction. London: Sage.

Mahyoob, M., Algaraady, J. and Alrahaili, M. (2021). Linguistic-based detection of fake news in social media. International Journal of English Linguistics 11(1): 99–109. [Online URL:] accessed on September 8, 2021.

Markowitz, D. M. and Hancock, J. T. (2014). Linguistic traces of a scientific fraud: The case of Diederik Stapel. PloS One 9(8): e105937. [Online URL:] accessed on May 4, 2021.

Martin, J. R. and Rose, D. (2007). Working with Discourse: Meaning Beyond the Clause. London: Bloomsbury.

Medford, R. J., Saleh, S. N., Sumarsono, A., Perl, T. M. and Lehmann, C. U. (2020). An “infodemic”: leveraging high-volume Twitter data to understand early public sentiment for the coronavirus disease 2019 outbreak. Open Forum Infectious Diseases 7(7): ofaa258. [Online URL:] accessed on June 14, 2021.

Meyer, B. (2015). Case Studies. In C. V. Angelelli and B. J. Baer (Eds.), Researching Translation and Interpreting, pp. 177–184. London: Routledge.

Mookdarsanit, P. and Mookdarsanit, L. (2021). The COVID-19 fake news detection in Thai social texts. Bulletin of Electrical Engineering and Informatics 10(2): 988–998. [Online URL:] accessed on September 8, 2021.

Munday, J. (2007). Translation and ideology: A textual approach. The Translator 13(2): 195–217. [Online URL:] accessed on July 24, 2021.

Munday, J. (2012). Evaluation in Translation: Critical Points of Translator Decision-Making. London: Routledge.

Munday, J. (2018). A model of appraisal: Spanish interpretations of President Trump’s inaugural address 2017. Perspectives 26(2): 180–195. [Online URL:] accessed on June 14, 2021.

Munday, J. and Zhang, M. (2017). Introduction. In J. Munday and M. Zhang (Eds.), Discourse Analysis in Translation Studies, pp. 1–10. Amsterdam: John Benjamins Publishing.

Ophir, Y. (2018). Spreading News: The Coverage of Epidemics by American Newspapers and Its Effects on Audiences - A Crisis Communication Approach. Doctoral dissertation. University of Pennsylvania, USA. [Online URL:] accessed on June 14, 2021.

O’Sullivan, C. (2010). Pseudotranslation. In Y. Gambier and L. van Doorslaer (Eds.), Handbook of Translation Studies, Volume 2, pp. 123–125. Amsterdam: John Benjamins Publishing.

Pennycook, G., McPhetres, J., Zhang, Y., Lu, J. G. and Rand, D. G. (2020). Fighting COVID-19 misinformation on social media: Experimental evidence for a scalable accuracy-nudge intervention. Psychological Science 31(7): 770–780. [Online URL:] accessed on May 4, 2021.

Ping, Y. (2018). News translation in the representations of Hong Kong: A critical narrative analysis of the Legislative Council oath-taking controversy. Asia Pacific Translation and Intercultural Studies 5(3): 231–249. [Online URL:] accessed on June 14, 2021.

Qin, B. and Zhang, M. (2020). Taking mediated stance via news headline transediting: A case study of the China-U.S. trade conflict in 2018. Meta 65(1): 100–122. [Online URL:] accessed on July 24, 2021.

Rambelli, P. (2019). Pseudotranslation. In M. Baker and G. Saldanha (Eds.), Routledge Encyclopedia of Translation Studies. 3rd ed., pp. 441–445. London: Routledge.

Rath, B. (2017). Pseudotranslation. In U. K. Heise (Ed.), Futures of Comparative Literature: ACLA State of the Discipline Report, pp. 230–233. London: Routledge.

Rubin, V., Conroy, N., Chen, Y. and Cornwell, S. (2016). Fake News or truth? Using Satirical Cues to Detect Potentially Misleading News. In T. Fornaciari, E. Fitzpatrick and J. Bachenko (Eds.), Proceedings of The Second Workshop on Computational Approaches to Deception Detection, pp. 7–17. Stroudsburg, PA: Association for Computational Linguistics. [Online URL:] accessed on May 4, 2021.

Ruchansky, N., Seo, S. and Liu, Y. (2017). Csi: A Hybrid Deep Model for Fake News Detection. In E.-P. Lim et al. (Chairs), CIKM '17: Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, pp. 797–806. New York: Association for Computing Machinery. [Online URL:] accessed on May 4, 2021.

Sa-nga-ngam, P., Mayakul, T., Srisawat, W. and Kiattisin, S. (2019). Fake news and online disinformation. A perspectives of Thai government officials. Paper presented at The 4th Technology Innovation Management and Engineering Science International Conference (TIMES-iCON), Bangkok, Thailand. December 11–13. [Online URL:] accessed on April 5, 2021.

Sombatpoonsiri, J. (2021). 6. Securitizing “Fake News”: Policy Responses to Disinformation in Thailand. In A. Sinpen and R. Tapsell (Eds.), From Grassroots Activism to Disinformation: Social Media Trends in Southeast Asia, pp. 105–125. Singapore: ISEAS Publishing.

Shu, K., Sliva, A., Wang, S., Tang, J. and Liu, H. (2017). Fake news detection on social media: A data mining perspective. ACM SIGKDD Explorations Newsletter 19(1): 22–36. [Online URL:] accessed on May 4, 2021.

Shu, K., Wang, S., Le, T., Lee, D. and Liu, H. (2018). Deep Headline Generation for ClickBait Detection. In F. Zhu and J. Yu (Chairs), 2018 IEEE International Conference on Data Mining, (ICDM), pp. 467–476. New Jersey: IEEE. [Online URL:] accessed on May 4, 2021.

Siwapathomchai, S. (2021). Thai children’s new media use at home: Intra-family communication and reverse socialisation. Journal of Language and Culture 40(2): 166–196. [Online URL:] accessed on September 8, 2021.

Stetting, K. (1989). Transediting – A New Term for Coping with the Grey Area Between Editing and Translating. In G. Caie (Ed.), Proceedings from the Fourth Nordic Conference for English Studies, pp. 371–382. Copenhagen: University of Copenhagen.

Tandoc, C. C. Jr., Lim, Z. W. and Ling, R. (2018). Defining “fake news”: A typology of scholarly definitions. Digital Journalism 6(2): 137–153. [Online URL:] accessed on May 4, 2021.

Tasnim, S., Hossain, M. M. and Mazumder, H. (2020). Impact of rumors and misinformation on COVID-19 in social media. Journal of Preventive Medicine and Public Health 53(3): 171–174. [Online URL:] accessed on July 24, 2021.

Thaweephol, P. and Saisuwan, P. (2021). Attitudes towards Thai-English code-switching among Thai speakers in Generation Y. Journal of Language and Culture 40(2): 53–78. [Online URL:] accessed on September 8, 2021.

Valdeón, R. A. (2009). Translating informative and persuasive texts. Perspective 17(2): 77–81. [Online URL:] accessed on June 14, 2021.

Valdeón, R. A. (2016). The Construction of National Images Through News Translation. In L. van Doorslaer, P. Flynn and J. Leerssen (Eds.), Interconnecting Translation Studies and Imagology, pp. 219–237. Amsterdam: John Benjamins Publishing.

Van Dijk, T. A. (2008). Discourse and Power. New York: Palgrave Macmillan.

Veszelszki, Á. (2017). Linguistic and non-linguistic elements in detecting (Hungarian) fake news. Acta Universitatis Sapientiae, Communicatio 4(1): 7–35. [Online URL:] accessed on January 12, 2021.

Waszak, P. M., Kasprzycka-Waszak, W. and Kubanek, A. (2018). The spread of medical fake news in social media – The pilot quantitative study. Health Policy and Technology 7(2): 115–118. [Online URL:] accessed on January 12, 2021.

White, S. J. (2019). Conversation Analysis: An Introduction to Methodology, Data Collection, and Analysis. In P. Liamputtong (Ed.), Handbook of Research Methods in Health Social Sciences, pp. 471-490. Singapore: Springer.

Wong, J. E. L., Leo, Y. S. and Tan, C. C. (2020). COVID-19 in Singapore—current experience: Critical global issues that require attention and action. JAMA 323(13): 1243–1244. [Online URL:] accessed on May 4, 2021.

World Health Organization. (2020). Munich Security Conference. [Online URL:] accessed on September 1, 2021.

Yang, K.-C., Pierri, F., Hui, P.-M., Axelrod, D., Torres-Lugo, C., Bryden, J. and Menczer, F. (2021). The COVID-19 infodemic: Twitter versus Facebook. Big Data & Society 8(1). [Online URL:] accessed on September 1, 2021.

Yang, Y. and Su, Y. (2020). Public voice via social media: Role in cooperative governance during public health emergency. International Journal of Environmental Research and Public Health 17(18): 6840. [Online URL:] accessed on September 8, 2021.

Zhang, M., Pan, H., Chen, X. and Luo, T. (2015). Mapping discourse analysis in translation studies via bibliometrics: A survey of journal publications. Perspectives 23(2): 223–239. [Online URL:] accessed on June 14, 2021.