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Skip search results from other journals and go to results- 2 Journal of Medical Internet Research
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Twitter Misinformation Discourses About Vaping: Systematic Content Analysis
Allem et al [7], for example, warned that social bots may also perpetuate this narrative through misleading web-based discourse. Social bots are prominent on Twitter, where they produce large numbers of tweets, saturate certain areas of social discourse, and are often linked to the spread of misinformation [13,14]. Overall, 1 study [12] found that over 41% of tweets that shared information about vaping contained at least 1 piece of possible misinformation [12].
J Med Internet Res 2023;25:e49416
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Investigation of COVID-19 Misinformation in Arabic on Twitter: Content Analysis
In 1 example, retweeted 471 times, the user argues that a citizen died following a vaccine shot, tagging and attacking Kuwait’s former health minister Basel Al Sabah. The tweet says:
Dr. Basil @drbaselalsabah. A citizen took the vaccine and suffered a stroke and today she died. Do you still want to force people to be vaccinated! The tragedy is that there was a doctor mocking her condition and considered it a figment of her imagination.
JMIR Infodemiology 2022;2(2):e37007
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Sex Workers’ Lived Experiences With COVID-19 on Social Media: Content Analysis of Twitter Posts
JMIR Form Res 2022;6(7):e36268
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COVID-19 and the Gendered Use of Emojis on Twitter: Infodemiology Study
Further, Tossell et al [31] investigated how emoticons were used and, in particular, how gender differences exist in the frequency and variety of emoticons. For their analysis, data from 21 smartphones was taken over a 6-month period. In terms of quantity, the authors observed that women were more likely to use emoticons than men, while the latter preferred using a distinct range of emoticons to express themselves.
J Med Internet Res 2020;22(11):e21646
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