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

JMIR Theme Issue: COVID-19 Special Issue (2452) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1641) Infodemiology and Infoveillance (1349) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041) Natural Language Processing (692) Outbreak and Pandemic Preparedness and Management (1727) Infectious Diseases (non-STD/STI) (1575) Machine Learning (1465) Quality/Credibility of eHealth Information and Trust Issues (531) Information Quality in Digital Media (340)

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

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/26302, first published .
Using Tweets to Understand How COVID-19–Related Health Beliefs Are Affected in the Age of Social Media: Twitter Data Analysis Study

Using Tweets to Understand How COVID-19–Related Health Beliefs Are Affected in the Age of Social Media: Twitter Data Analysis Study

Using Tweets to Understand How COVID-19–Related Health Beliefs Are Affected in the Age of Social Media: Twitter Data Analysis Study

Authors of this article:

Hanyin Wang1 Author Orcid Image ;   Yikuan Li1 Author Orcid Image ;   Meghan Hutch1 Author Orcid Image ;   Andrew Naidech2 Author Orcid Image ;   Yuan Luo1 Author Orcid Image
Article Authors Cited by (36) Tweetations (26) Metrics

Journals

  1. Reuter K, Deodhar A, Makri S, Zimmer M, Berenbaum F, Nikiphorou E. The impact of the COVID-19 pandemic on people with rheumatic and musculoskeletal diseases: insights from patient-generated data on social media. Rheumatology 2021;60(SI):SI77 View
  2. Khan M, Shahzad S. Deconstructing the Problematic Roles of Pakistani Media During the Covid-19 Pandemic. SSRN Electronic Journal 2021 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. Ke S, Neeley-Tass E, Barnes M, Hanson C, Giraud-Carrier C, Snell Q. COVID-19 Health Beliefs Regarding Mask Wearing and Vaccinations on Twitter: Deep Learning Approach. JMIR Infodemiology 2022;2(2):e37861 View
  5. Storey V, O’Leary D. Text Analysis of Evolving Emotions and Sentiments in COVID-19 Twitter Communication. Cognitive Computation 2024;16(4):1834 View
  6. Venuturupalli S, Kumar A, Bunyan A, Davuluri N, Fortune N, Reuter K. Using Patient‐Reported Health Data From Social Media to Identify Diverse Lupus Patients and Assess Their Symptom and Medication Expressions: A Feasibility Study. Arthritis Care & Research 2023;75(2):365 View
  7. Wang D, Lu J, Zhong Y. Futile or fertile? The effect of persuasive strategies on citizen engagement in COVID-19 vaccine-related tweets across six national health departments. Social Science & Medicine 2023;317:115591 View
  8. Liu T, Xiao X. A Framework of AI-Based Approaches to Improving eHealth Literacy and Combating Infodemic. Frontiers in Public Health 2021;9 View
  9. Crema C, Attardi G, Sartiano D, Redolfi A. Natural language processing in clinical neuroscience and psychiatry: A review. Frontiers in Psychiatry 2022;13 View
  10. Shoeibi N, Shoeibi N, Chamoso P, Alizadehsani Z, Corchado J. A Hybrid Model for the Measurement of the Similarity between Twitter Profiles. Sustainability 2022;14(9):4909 View
  11. Chen L, Miao M, Rajakani K. Application of Decision Tree Intelligent Algorithm in Data Analysis of Physical Health Test. Journal of Healthcare Engineering 2022;2022:1 View
  12. Mao Z, Wang D, Zheng S. Health belief model and social media engagement: A cross-national study of health promotion strategies against COVID-19 in 2020. Frontiers in Public Health 2023;11 View
  13. Fadda M, Camerini A, Fiordelli M, Corna L, Levati S, Amati R, Piumatti G, Crivelli L, Suggs L, Albanese E. Why Vaccinate Against COVID-19? A Population-Based Survey in Switzerland. International Journal of Public Health 2022;67 View
  14. Meppelink C, Bos L, Boukes M, Möller J. A Health Crisis in the Age of Misinformation: How Social Media and Mass Media Influenced Misperceptions about COVID-19 and Compliance Behavior. Journal of Health Communication 2022;27(10):764 View
  15. McNulty C, Read B, Quigley A, Verlander N, Lecky D. What the public in England know about antibiotic use and resistance in 2020: a face-to-face questionnaire survey. BMJ Open 2022;12(4):e055464 View
  16. Chen Y, Zhang Z. An easy numeric data augmentation method for early-stage COVID-19 tweets exploration of participatory dynamics of public attention and news coverage. Information Processing & Management 2022;59(6):103073 View
  17. Tawat M. Fake News and COVID-19 Vaccine Hesitancy: A Study of Practices and Sociopolitical Implications in Cameroon. SSRN Electronic Journal 2021 View
  18. Chum A, Nielsen A, Bellows Z, Farrell E, Durette P, Banda J, Cupchik G. Changes in Public Response Associated With Various COVID-19 Restrictions in Ontario, Canada: Observational Infoveillance Study Using Social Media Time Series Data. Journal of Medical Internet Research 2021;23(8):e28716 View
  19. Wang D, Lu J. How News Agencies’ Twitter Posts on COVID-19 Vaccines Attract Audiences’ Twitter Engagement: A Content Analysis. International Journal of Environmental Research and Public Health 2022;19(5):2716 View
  20. Wang H, Li Y, Hutch M, Kline A, Otero S, Mithal L, Miller E, Naidech A, Luo Y. Patterns of diverse and changing sentiments towards COVID-19 vaccines: a sentiment analysis study integrating 11 million tweets and surveillance data across over 180 countries. Journal of the American Medical Informatics Association 2023;30(5):923 View
  21. Singhal A, Mago V. Exploring How Healthcare Organizations Use Twitter: A Discourse Analysis. Informatics 2023;10(3):65 View
  22. Hertz M, Dierst-Davies R, Freire K, Verlenden J, Whitton L, Zimmerman J, Honeycutt S, Puddy R, Baldwin G. Design and Implementation of an Innovative, Rapid Data-Monitoring Strategy for Public Health Emergencies: Pilot of the United States School COVID-19 Mitigation Strategies Project. Public Health Reports® 2023;138(6):878 View
  23. Competiello S, Bizer G, Walker D. The Power of Social Media: Stigmatizing Content Affects Perceptions of Mental Health Care. Social Media + Society 2023;9(4) View
  24. Sharma T, Farea A, Perera N, Emmert-Streib F. Exploring COVID-related relationship extraction: Contrasting data sources and analyzing misinformation. Heliyon 2024;10(5):e26973 View
  25. Luo Y, Mao C, Sanchez‐Pinto L, Ahmad F, Naidech A, Rasmussen L, Pacheco J, Schneider D, Mithal L, Dresden S, Holmes K, Carson M, Shah S, Khan S, Clare S, Wunderink R, Liu H, Walunas T, Cooper L, Yue F, Wehbe F, Fang D, Liebovitz D, Markl M, Michelson K, McColley S, Green M, Starren J, Ackermann R, D'Aquila R, Adams J, Lloyd‐Jones D, Chisholm R, Kho A. Northwestern University resource and education development initiatives to advance collaborative artificial intelligence across the learning health system. Learning Health Systems 2024;8(3) View
  26. Jokanovic I, Canham H. The operation of ideology in coronavirus vaccine Twitter influencer commentary. Discourse & Communication 2024 View
  27. Jaballi S, Hazar M, Zrigui S, Mahjoubi A, Nicolas H, Zrigui M, Bhadu M. Decoding Multilingual Topic Dynamics and Trend Identification through ARIMA Time Series Analysis on Social Networks: A Novel Data Translation Framework Enhanced by LDA/HDP Models. Journal of Electrical and Computer Engineering 2024;2024(1) View
  28. Oh S, Syn S. Perceived risks and use of social media for COVID-19 information. Library Hi Tech 2024 View

Books/Policy Documents

  1. Xu H, Curci M, Ek S, Liu P, Li Z, Xu S. Cloud Computing – CLOUD 2021. View