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Citing this Article

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Published on 21.04.20 in Vol 6, No 2 (2020): Apr-Jun

This paper is in the following e-collection/theme issue:

Works citing "Data Mining and Content Analysis of the Chinese Social Media Platform Weibo During the Early COVID-19 Outbreak: Retrospective Observational Infoveillance Study"

According to Crossref, the following articles are citing this article (DOI 10.2196/18700):

(note that this is only a small subset of citations)

  1. Pobiruchin M, Zowalla R, Wiesner M. Temporal and Location Variations, and Link Categories for the Dissemination of COVID-19–Related Information on Twitter During the SARS-CoV-2 Outbreak in Europe: Infoveillance Study. Journal of Medical Internet Research 2020;22(8):e19629
    CrossRef
  2. Picone M, Inoue S, DeFelice C, Naujokas MF, Sinrod J, Cruz VA, Stapleton J, Sinrod E, Diebel SE, Wassman ER. Social Listening as a Rapid Approach to Collecting and Analyzing COVID-19 Symptoms and Disease Natural Histories Reported by Large Numbers of Individuals. Population Health Management 2020;
    CrossRef
  3. Zhang D, Zhou L, Lim J. From Networking to Mitigation: The Role of Social Media and Analytics in Combating the COVID-19 Pandemic. Information Systems Management 2020;:1
    CrossRef
  4. Campos-Castillo C, Laestadius LI. Racial and Ethnic Digital Divides in Posting COVID-19 Content on Social Media Among US Adults: Secondary Survey Analysis. Journal of Medical Internet Research 2020;22(7):e20472
    CrossRef
  5. Liao Q, Yuan J, Dong M, Yang L, Fielding R, Lam WWT. Public Engagement and Government Responsiveness in the Communications About COVID-19 During the Early Epidemic Stage in China: Infodemiology Study on Social Media Data. Journal of Medical Internet Research 2020;22(5):e18796
    CrossRef
  6. Shen C, Chen A, Luo C, Zhang J, Feng B, Liao W. Using Reports of Symptoms and Diagnoses on Social Media to Predict COVID-19 Case Counts in Mainland China: Observational Infoveillance Study. Journal of Medical Internet Research 2020;22(5):e19421
    CrossRef
  7. Mackey T, Purushothaman V, Li J, Shah N, Nali M, Bardier C, Liang B, Cai M, Cuomo R. Machine Learning to Detect Self-Reporting of Symptoms, Testing Access, and Recovery Associated With COVID-19 on Twitter: Retrospective Big Data Infoveillance Study. JMIR Public Health and Surveillance 2020;6(2):e19509
    CrossRef
  8. Ahmed W, Vidal-Alaball J, Downing J, López Seguí F. COVID-19 and the 5G Conspiracy Theory: Social Network Analysis of Twitter Data. Journal of Medical Internet Research 2020;22(5):e19458
    CrossRef
  9. Peng Z, Wang R, Liu L, Wu H. Exploring Urban Spatial Features of COVID-19 Transmission in Wuhan Based on Social Media Data. ISPRS International Journal of Geo-Information 2020;9(6):402
    CrossRef
  10. Walrave M, Waeterloos C, Ponnet K. Adoption of a Contact Tracing App for Containing COVID-19: A Health Belief Model Approach. JMIR Public Health and Surveillance 2020;6(3):e20572
    CrossRef
  11. Eltoukhy AEE, Shaban IA, Chan FTS, Abdel-Aal MAM. Data Analytics for Predicting COVID-19 Cases in Top Affected Countries: Observations and Recommendations. International Journal of Environmental Research and Public Health 2020;17(19):7080
    CrossRef