| Literature DB >> 35731969 |
Cindy Sing Bik Ngai1, Rita Gill Singh2, Le Yao1.
Abstract
BACKGROUND: Vaccines serve an integral role in containing pandemics, yet vaccine hesitancy is prevalent globally. One key reason for this hesitancy is the pervasiveness of misinformation on social media. Although considerable research attention has been drawn to how exposure to misinformation is closely associated with vaccine hesitancy, little scholarly attention has been given to the investigation or robust theorizing of the various content themes pertaining to antivaccine misinformation about COVID-19 and the writing strategies in which these content themes are manifested. Virality of such content on social media exhibited in the form of comments, shares, and reactions has practical implications for COVID-19 vaccine hesitancy.Entities:
Keywords: COVID-19; antivaccine misinformation; content analysis; content themes; social media; virality; writing strategies
Mesh:
Substances:
Year: 2022 PMID: 35731969 PMCID: PMC9301555 DOI: 10.2196/37806
Source DB: PubMed Journal: J Med Internet Res ISSN: 1438-8871 Impact factor: 7.076
Description of the six subdimensions and their references.
| Dimensions and subdimensions | Descriptions | References | ||
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| Safety | Posts that discredit the safety of vaccines (eg, vaccines can cause harm or death) | [ | |
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| Conspiracy | Posts that highlight specific conspiracy theories (eg, stories of fake claims of microchips found in vaccines; fraud; collusion between pharmaceutical companies, governments, and doctors; and pharmaceutical companies manipulating data to reap huge profits) | [ | |
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| Efficacy | Posts that advocate vaccines as ineffective and unnecessary, emphasizing that they are unsuccessful and an increased incidence in the disease is seen after vaccination | [ | |
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| Format and language features mimicking news or scientific reports | Posts that mimic the format and other features typical of real news or scientific reports. This is exhibited in the following ways: capitalizing all letters of the first word (eg, BREAKING, JUST IN); describing actions and quoting sentences from public figures; attributing information to credible-sounding sources, including medical experts, doctors/nurses, scientific studies, legal documents; using jargon, terminology, and/or statistics | [ | |
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| Conversational style | Posts that are characterized by a conversational style or an informal, personal tone of voice. This is exhibited in: first- or second-person address form (eg, we should listen, you must act...); author visibility such as sharing personal experiences and feelings; and use of informal expressions (eg, using sentence fragments, questions, contractions, emojis, swear words) | [ | |
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| Amplification | Strategies used to amplify or exaggerate the message. This is exhibited in the use of hashtags and @messages to celebrities and public figures | [ | |
Descriptive statistics on the examination of content themes disseminated in COVID-19 vaccine misinformation posts on Facebook.
| Content theme | Number of posts | Mean (SD) |
| Safety concern | 140 | 0.23 (0.30) |
| Conspiracy theories | 140 | 0.13 (0.25) |
| Vaccine efficacy | 140 | 0.04 (0.14) |
| Total | 420 | 0.13 (0.25) |
Figure 1Mean count of sentences disseminating content themes (CT) in COVID-19 vaccine misinformation posts on Facebook.
Descriptive statistics on the examination of writing strategies employed in COVID-19 vaccine misinformation posts on Facebook.
| Writing strategies | Number of posts | Mean (SD) |
| Format or language features mimicking news or scientific reports | 140 | 0.29 (0.32) |
| Conversational style | 140 | 0.45 (0.36) |
| Amplification | 140 | 0.07 (0.16) |
| Total | 420 | 0.27 (0.33) |
Figure 2Mean count of sentences employing writing strategies in COVID-19 vaccine misinformation (MS) posts on Facebook.
Identification of positive and negative predictors of the numbers of likes, comments, and shares using a negative binomial regression model.
| Variables | Likes | Comments | Shares | ||||||||
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| β (SE) | 95% CI | β (SE) | 95% CI | β (SE) | 95% CI | |||||
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| Safety concern | –3.04 (0.52) | –4.07 to –2.02 | <.001 | –1.52 (.48) | –2.45 to –.59 | .001 | –1.19 (.55) | –2.27 to –.12 | .03 | |
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| Conspiracy theories | .35 (.58) | –.79 to 1.49 | .55 | .06 (.51) | –.94 to 1.06 | .90 | .53 (.59) | –.63 to 1.70 | .37 | |
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| Efficacy | .22 (.83) | –1.40 to 1.84 | .79 | –.02 (.80) | –1.59 to 1.55 | .98 | –.32 (.89) | –2.06 to 1.42 | .72 | |
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| Format or language features mimicking news or scientific reports | 2.02 (.93) | .19 to 3.85 | .03 | –.10 (.79) | –1.66 to 1.46 | .90 | –.20 (.75) | –1.68 to 1.28 | .79 | |
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| Conversational style | .23 (.74) | –1.21 to 1.68 | .75 | .23 (.69) | –1.12 to 1.58 | .74 | .26 (.73) | –1.18 to 1.70 | .72 | |
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| Amplification | .51 (1.16) | –1.76 to 2.77 | .66 | –.35 (1.03) | –2.36 to 1.67 | .74 | .70 (1.22) | –1.70 to 3.10 | .57 | |