Ha-Linh Quach, Thai Quang Pham, Ngoc Anh Hoang, Dinh Cong Phung, Viet Cuong Nguyen, Son Hong Le, Thanh Cong Le, Dang Hai Le, Anh Duc Dang, Duong Nhu Tran, Nghia Duy Ngu, Florian Vogt, Cong Khanh Nguyen
Healthcare Informatics Research
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.
Ha-Linh Quach, Thai Quang Pham, Ngoc-Anh Hoang, Dinh Cong Phung, Viet Cuong Nguyen, Son Hong Le, Thanh Cong Le, Thu Minh Thi Bui, Dang Hai Le, Anh Duc Dang, Duong Nhu Tran, Nghia Duy Ngu, Florian Vogt, Cong Khanh Nguyen
Background Trends in the public perception and awareness of COVID-19 over time are poorly understood. We conducted a longitudinal study to analyze characteristics and trends of online information during a major COVID-19 outbreak in Da Nang province, Vietnam in July-August 2020 to understand public awareness and perceptions during an epidemic. Methods We collected online information on COVID-19 incidence and mortality from online platforms in Vietnam between 1 July and 15 September, 2020, and assessed their trends over time against the epidemic curve. We explored the associations between engagement, sentiment polarity, and other characteristics of online information with different outbreak phases using Poisson regression and multinomial logistic regression analysis. We assessed the frequency of keywords over time, and conducted a semantic analysis of keywords using word segmentation Results
We found a close association between collected online information and the evolution of the
COVID-19 situation in Vietnam. Online information generated higher engagements during
compared to before the outbreak. There was a close relationship between sentiment polarity
and posts’ topics: the emotional tendencies about COVID-19 mortality were significantly
more negative, and more neutral or positive about COVID-19 incidence. Online newspaper
reported significantly more information in negative or positive sentiment than online forums
or social media. Most topics of public concern followed closely the progression of the
COVID-19 situation during the outbreak: development of the global pandemic and vaccination; the unfolding outbreak in Vietnam; and the subsiding of the outbreak after two months.
Conclusion
This study shows how online information can reflect a public health threat in real time, and
provides important insights about public awareness and perception during different outbreak
phases. Our findings can help public health decision makers in Vietnam and other low and
middle income countries with high internet penetration rates to design more effective communication strategies during critical phases of an epidemic
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