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Literature DB >> 28343702

Yellow fever outbreaks and Twitter: Rumors and misinformation.

Yeimer Ortiz-Martínez¹, Luisa F Jiménez-Arcia².

Abstract

Entities: Disease

Mesh：

Year: 2017 PMID： 28343702 DOI： 10.1016/j.ajic.2017.02.027

Source DB: PubMed Journal: Am J Infect Control ISSN： 0196-6553 Impact factor: 2.918

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Cited

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9 in total

1. Accuracy of health-related information regarding COVID-19 on Twitter during a global pandemic.

Authors: Sarah B Swetland; Ava N Rothrock; Halle Andris; Bennett Davis; Linh Nguyen; Phil Davis; Steven G Rothrock
Journal: World Med Health Policy Date: 2021-07-29

Review 2. 'Falsehood flies, and the truth comes limping after it': social media and public health.

Authors: Justin B Moore; Jenine K Harris; Ellen T Hutti
Journal: Curr Opin Psychiatry Date: 2021-09-01 Impact factor: 4.787

3. Yellow fever in the Americas: the growing concern about new epidemics.

Authors: Yeimer Ortiz-Martínez; Andrés Mauricio Patiño-Barbosa; Alfonso J Rodriguez-Morales
Journal: F1000Res Date: 2017-03-30

4. Nature and Diffusion of COVID-19-related Oral Health Information on Chinese Social Media: Analysis of Tweets on Weibo.

Authors: Zhuo-Ying Tao; Guang Chu; Colman McGrath; Fang Hua; Yiu Yan Leung; Wei-Fa Yang; Yu-Xiong Su
Journal: J Med Internet Res Date: 2020-06-15 Impact factor: 5.428

Yellow fever outbreaks and Twitter: Rumors and misinformation.

1. Accuracy of health-related information regarding COVID-19 on Twitter during a global pandemic.

Review 2. 'Falsehood flies, and the truth comes limping after it': social media and public health.

3. Yellow fever in the Americas: the growing concern about new epidemics.

4. Nature and Diffusion of COVID-19-related Oral Health Information on Chinese Social Media: Analysis of Tweets on Weibo.

5. Coronavirus Goes Viral: Quantifying the COVID-19 Misinformation Epidemic on Twitter.

6. COVID-19-Related Web Search Behaviors and Infodemic Attitudes in Italy: Infodemiological Study.

7. Misinformation Dissemination in Twitter in the COVID-19 Era.

8. An exploratory study of COVID-19 misinformation on Twitter.

9. Identification of affective valence of Twitter generated sentiments during the COVID-19 outbreak.