| Literature DB >> 34007225 |
Kelin Chen1, Yuni Luo1, Anyang Hu2, Ji Zhao3, Liwei Zhang4.
Abstract
BACKGROUND: During a public health emergency, social media is a major conduit or vector for spreading health misinformation. Understanding the characteristics of health misinformation can be a premise for rebuking and purposefully correcting such misinformation on social media.Entities:
Keywords: COVID-19; China; health communication; health misinformation; public health emergency; social media
Year: 2021 PMID: 34007225 PMCID: PMC8121282 DOI: 10.2147/RMHP.S312327
Source DB: PubMed Journal: Risk Manag Healthc Policy ISSN: 1179-1594
Classification of the Misinformation Related to COVID-19 in China
| Type | Description | Example |
|---|---|---|
| Rumor | In this data, the term of rumor is used to represent completely fake news or messages that have been verified by government or expert. | The unknown pneumonia in Wuhan is the SARS virus. |
| No ultimate conclusion (controversial conclusion) | This type is almost equal to Swire-Thompson and Lazer’s definition that the message has not proven by the scientific community, and blindly following such messages may be ineffective or harmful. | Lopinavir/ritonavir can effectively remedy COVID-19. |
| Inaccuracy | The original or a part of the content of the message is genuine or factual; however, the final version of the message is processed or distorted. | If a disinfectant’s name involves chlorine, it is a chlorine-containing disinfectant. |
| Fake scientific knowledge (fake common knowledge) | The message has been proven wrong by the scientific community. | Fireworks can prevent the epidemic. |
| Dependent on the situation | Such a message is factual only in specific situations. | N95 masks should be changed every four hours. |
| Fake news | Created news for attracting clicks and followers, or for entertainment purposes. | Brazilian President Jair Bolsonaro was confirmed as having COVID-19. |
Note: Summarized from Real-Time Rumors Refuting of the Novel Coronavirus Pneumonia.35
Different COVID-19 Misinformation Contents
| Category | Explanation | Example | N | % |
|---|---|---|---|---|
| Preventive and therapeutic methods | Curative medicine and preventive methods of COVID-19. | 234 | 42.78 | |
| Epidemiological characteristics of COVID-19 | Related epidemiological characteristics. | 53 | 9.69 | |
| Restoration of normal production and life | The date and schedule of restoring schooling, production, and living. | 32 | 5.85 | |
| International and domestic travel restrictions | Policies of travel restriction issued by China’s government and other countries’ governments. | 26 | 4.75 | |
| Domestic (China) outbreak situation | Severe situations and reappearances of COVID-19 in China. | 38 | 6.95 | |
| International outbreak situation | Severe situations of COVID-19 outbreak outside of China. | 24 | 4.39 | |
| Policies responding to COVID-19 | Official policies responding to COVID-19 issued by China’s multi-level governments. | 50 | 8.96 | |
| Confirmed cases of special people | Special people, such as celebrities, politicians, and medical workers, were confirmed as being infected. | 21 | 3.84 | |
| Conspiracy theories | Conspiracy theory associated with the virus source or biological warfare. | 11 | 2.01 | |
| Others | Fake news related to social life. | 59 | 10.79 | |
| Overall | 547 | 100 |
Note: Summarized from Real-Time Rumors Refuting of the Novel Coronavirus Pneumonia.35
Top-Ten Most Frequent Words of the COVID-19 Misinformation
| Keyword | Frequency (Count) | Weight | |
|---|---|---|---|
| 1 | Prevention | 58 | 0.8437 |
| 2 | Infection | 53 | 0.8391 |
| 3 | Mask | 48 | 0.8752 |
| 4 | Wuhan | 42 | 0.8143 |
| 5 | Therapy | 27 | 0.7631 |
| 6 | Disinfection | 25 | 0.7724 |
| 7 | American | 25 | 0.7399 |
| 8 | Patient | 20 | 0.7389 |
| 9 | School start | 18 | 0.7286 |
| 10 | Zhong Nanshan | 18 | 0.7312 |
Notes: p<0.01. Following instructions of the online software, the algorithm of “weight” is jointly determined by word frequency, resolving the power of words, and the level of semantic aggregation. Data came from Real-Time Rumors Refuting of the Novel Coronavirus Pneumonia.35 The online software is accessible via .
Comparison Between Traditional Chinese Medicine (TCM)- and Folk Prescription (FP)-Related Misinformation and Western Medicine (WM)-Related Misinformation
| Rumors | No Ultimate Conclusion (Controversial Conclusion) | Fake Scientific Knowledge (Fake Common Knowledge) | Total | |
|---|---|---|---|---|
| TCM | 4 | 12 | 2 | 18 (26.09%) |
| FP | 20 | 0 | 10 | 30 (43.48%) |
| WM | 11 | 8 | 2 | 21 (30.43%) |
| Total | 35 | 20 | 14 | 69 (100%) |
Note: Summarized from Real-Time Rumors Refuting of the Novel Coronavirus Pneumonia.35
Figure 1Timelines of misinformation and confirmed cases by using weekly data.
Figure 2Comparison of the trends of the misinformation of “Preventive and Therapeutic Methods” and “Restoration of Normal Production and Life.”