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

JMIR Theme Issue: COVID-19 Special Issue (2388)

Published on in Vol 23, No 2 (2021): February

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/25108, first published .
Understanding the Public Discussion About the Centers for Disease Control and Prevention During the COVID-19 Pandemic Using Twitter Data: Text Mining Analysis Study

Understanding the Public Discussion About the Centers for Disease Control and Prevention During the COVID-19 Pandemic Using Twitter Data: Text Mining Analysis Study

Understanding the Public Discussion About the Centers for Disease Control and Prevention During the COVID-19 Pandemic Using Twitter Data: Text Mining Analysis Study

Authors of this article:

Joanne Chen Lyu1 Author Orcid Image ;   Garving K Luli2 Author Orcid Image
Article Authors Cited by (27) Tweetations (6) Metrics

Journals

  1. Lyu J, Han E, Luli G. COVID-19 Vaccine–Related Discussion on Twitter: Topic Modeling and Sentiment Analysis. Journal of Medical Internet Research 2021;23(6):e24435 View
  2. Bok S, Shum J, Harvie J, Lee M. We versus me: Indirect conditional effects of collectivism on COVID-19 public policy hypocrisy. Journal of Entrepreneurship and Public Policy 2021;10(3):379 View
  3. Banda J, Tekumalla R, Wang G, Yu J, Liu T, Ding Y, Artemova E, Tutubalina E, Chowell G. A Large-Scale COVID-19 Twitter Chatter Dataset for Open Scientific Research—An International Collaboration. Epidemiologia 2021;2(3):315 View
  4. Mathayomchan B, Taecharungroj V, Wattanacharoensil W. Evolution of COVID-19 tweets about Southeast Asian Countries: topic modelling and sentiment analyses. Place Branding and Public Diplomacy 2023;19(3):317 View
  5. Melissa M, Jillian J, Jennifer E, Daniel G, Andrew P. Review and thematic analysis of guiding principles for effective crisis communication using social media. Journal of Public Health and Epidemiology 2022;14(2):72 View
  6. Tavana M, Shaabani A, Raeesi Vanani I, Kumar Gangadhari R. A Review of Digital Transformation on Supply Chain Process Management Using Text Mining. Processes 2022;10(5):842 View
  7. EKİN C, ÇAKICI M, ŞENER E, TÜRKER S, ALTANLAR S. Research Trends Analysis in Educational Journal Publications on Covid19 Using Descriptive and Text Mining Methods :Preliminary Analysis. European Journal of Science and Technology 2021 View
  8. Jafarzadeh H, Pauleen D, Abedin E, Weerasinghe K, Taskin N, Coskun M, Mehmood R. Making sense of COVID-19 over time in New Zealand: Assessing the public conversation using Twitter. PLOS ONE 2021;16(12):e0259882 View
  9. Drescher L, Roosen J, Aue K, Dressel K, Schär W, Götz A. The Spread of COVID-19 Crisis Communication by German Public Authorities and Experts on Twitter: Quantitative Content Analysis. JMIR Public Health and Surveillance 2021;7(12):e31834 View
  10. Koren A, Alam M, Koneru S, DeVito A, Abdallah L, Liu B. Nursing Perspectives on the Impacts of COVID-19: Social Media Content Analysis. JMIR Formative Research 2021;5(12):e31358 View
  11. Thakur N, Han C. An Exploratory Study of Tweets about the SARS-CoV-2 Omicron Variant: Insights from Sentiment Analysis, Language Interpretation, Source Tracking, Type Classification, and Embedded URL Detection. COVID 2022;2(8):1026 View
  12. Mihunov V, Jafari N, Wang K, Lam N, Govender D. Disaster Impacts Surveillance from Social Media with Topic Modeling and Feature Extraction: Case of Hurricane Harvey. International Journal of Disaster Risk Science 2022;13(5):729 View
  13. Yin M, Chen S, Pan X, Lu C, Lin X, Wang M, Ni J. Effects of Chinese provincial CDCs WeChat official account article features on user engagement during the COVID-19 pandemic. Journal of Global Health 2023;13 View
  14. Drescher L, Roosen J, Aue K, Dressel K, Schär W, Götz A. Emotionalität in der COVID-19-Krisenkommunikation von Behörden und unabhängigen Expert*innen auf Twitter. Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz 2023;66(6):689 View
  15. Mori Y, Miyatake N, Suzuki H, Mori Y, Okada S, Tanimoto K. Comparison of Impressions of COVID-19 Vaccination and Influenza Vaccination in Japan by Analyzing Social Media Using Text Mining. Vaccines 2023;11(8):1327 View
  16. Kasuga H, Endo S, Masuishi Y, Hidaka T, Kakamu T, Fukushima T. Public opinion in Japanese newspaper readers’ posts under the prolonged COVID-19 infection spread 2019–2021: contents analysis using Latent Dirichlet Allocation. Humanities and Social Sciences Communications 2023;10(1) View
  17. Fogarty B, Massie K, Svistova J. Unmasking twitter discourse: an infodemiology study of covid-19 mitigation practices. Atlantic Journal of Communication 2024;32(1):124 View
  18. Rathke B, Yu H, Huang H. What Remains Now That the Fear Has Passed? Developmental Trajectory Analysis of COVID-19 Pandemic for Co-occurrences of Twitter, Google Trends, and Public Health Data. Disaster Medicine and Public Health Preparedness 2023;17 View
  19. Thakur N. Investigating and Analyzing Self-Reporting of Long COVID on Twitter: Findings from Sentiment Analysis. Applied System Innovation 2023;6(5):92 View
  20. Shieh C, Nasongkhla J. Effects of motivation to use social networking sites on students’ media literacy and critical thinking. Online Journal of Communication and Media Technologies 2024;14(1):e202404 View
  21. Abdelaziz E, Alsadaan N, Alqahtani M, Elsharkawy N, Ouda M, Ramadan O, Shaban M, Shokre E. Effectiveness of Cognitive Behavioral Therapy (CBT) on Psychological Distress among Mothers of Children with Autism Spectrum Disorder: The Role of Problem-Solving Appraisal. Behavioral Sciences 2024;14(1):46 View
  22. HOCHIN H, YAMADA S, TAKEDA S. GRASPING THE REFERENCE RELATIONSHIPS BETWEEN OPINIONS IN WORKSHOP USING THE LADDERING METHOD. Journal of Architecture and Planning (Transactions of AIJ) 2024;89(816):445 View

Books/Policy Documents

  1. Ibrahim S, Abdallah S. Proceedings of the 2nd International Conference on Emerging Technologies and Intelligent Systems. View
  2. Nie A, Jiang H, Xu J, Fan J. E-Business. Digital Empowerment for an Intelligent Future. View
  3. Schmidt M, Dluzen D. Rigor and Reproducibility in Genetics and Genomics. View