Understanding the COVID-19 Infodemic: Analyzing User-Generated Online Information During a COVID-19 Outbreak in Vietnam.

Autor:	Quach HL; Department of Communicable Diseases Control, National Institute of Hygiene and Epidemiology, Hanoi, Vietnam.; National Centre for Epidemiology and Population Health, Research School of Population Health, College of Health and Medicine, Australian National University, Canberra, Australia., Pham TQ; Department of Communicable Diseases Control, National Institute of Hygiene and Epidemiology, Hanoi, Vietnam.; Department of Biostatistics and Medical Informatics, School of Preventive Medicine and Public Health, Hanoi Medical University, Hanoi, Vietnam., Hoang NA; Department of Communicable Diseases Control, National Institute of Hygiene and Epidemiology, Hanoi, Vietnam.; National Centre for Epidemiology and Population Health, Research School of Population Health, College of Health and Medicine, Australian National University, Canberra, Australia., Phung DC; National Agency for Science and Technology Information, Ministry of Science and Technology, Hanoi, Vietnam., Nguyen VC; HPC Systems Inc., Tokyo, Japan., Le SH; CMetric JSC Inc., Hanoi, Vietnam., Le TC; INFORE Technology Inc., Hanoi, Vietnam., Le DH; Department of Communicable Diseases Control, National Institute of Hygiene and Epidemiology, Hanoi, Vietnam., Dang AD; National Institute of Hygiene and Epidemiology, Hanoi, Vietnam., Tran DN; National Institute of Hygiene and Epidemiology, Hanoi, Vietnam., Ngu ND; Department of Communicable Diseases Control, National Institute of Hygiene and Epidemiology, Hanoi, Vietnam., Vogt F; National Centre for Epidemiology and Population Health, Research School of Population Health, College of Health and Medicine, Australian National University, Canberra, Australia.; The Kirby Institute, University of New South Wales, Sydney, Australia., Nguyen CK; Department of Communicable Diseases Control, National Institute of Hygiene and Epidemiology, Hanoi, Vietnam.; Field Epidemiology Training Program, National Institute of Hygiene and Epidemiology, Hanoi, Vietnam.
Jazyk:	angličtina
Zdroj:	Healthcare informatics research [Healthc Inform Res] 2022 Oct; Vol. 28 (4), pp. 307-318. Date of Electronic Publication: 2022 Oct 31.
DOI:	10.4258/hir.2022.28.4.307
Abstrakt:	Objectives: Online misinformation has reached unprecedented levels during the coronavirus disease 2019 (COVID-19) pandemic. This study analyzed the magnitude and sentiment dynamics of misinformation and unverified information about public health interventions during a COVID-19 outbreak in Da Nang, Vietnam, between July and September 2020. Methods: We analyzed user-generated online information about five public health interventions during the Da Nang outbreak. We compared the volume, source, sentiment polarity, and engagements of online posts before, during, and after the outbreak using negative binomial and logistic regression, and assessed the content validity of the 500 most influential posts. Results: Most of the 54,528 online posts included were generated during the outbreak (n = 46,035; 84.42%) and by online newspapers (n = 32,034; 58.75%). Among the 500 most influential posts, 316 (63.20%) contained genuine information, 10 (2.00%) contained misinformation, 152 (30.40%) were non-factual opinions, and 22 (4.40%) contained unverifiable information. All misinformation posts were made during the outbreak, mostly on social media, and were predominantly negative. Higher levels of engagement were observed for information that was unverifiable (incidence relative risk [IRR] = 2.83; 95% confidence interval [CI], 1.33-0.62), posted during the outbreak (before: IRR = 0.15; 95% CI, 0.07-0.35; after: IRR = 0.46; 95% CI, 0.34-0.63), and with negative sentiment (IRR = 1.84; 95% CI, 1.23-2.75). Negatively toned posts were more likely to be misinformation (odds ratio [OR] = 9.59; 95% CI, 1.20-76.70) or unverified (OR = 5.03; 95% CI, 1.66-15.24). Conclusions: Misinformation and unverified information during the outbreak showed clustering, with social media being particularly affected. This indepth assessment demonstrates the value of analyzing online "infodemics" to inform public health responses.
Databáze:	MEDLINE
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