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

JMIR Theme Issue: COVID-19 Special Issue (2548) Infodemiology and Infoveillance (1554) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1903) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1133) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1541) Natural Language Processing (899) Information Quality in Digital Media (404) Vaccination and Immunization in the Digital Age (441) Quality/Credibility of eHealth Information and Trust Issues (649)

Published on in Vol 24, No 10 (2022): October

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/40408, first published .
Fine-tuned Sentiment Analysis of COVID-19 Vaccine–Related Social Media Data: Comparative Study

Fine-tuned Sentiment Analysis of COVID-19 Vaccine–Related Social Media Data: Comparative Study

Fine-tuned Sentiment Analysis of COVID-19 Vaccine–Related Social Media Data: Comparative Study

Authors of this article:

Chad A Melton1, 2 Author Orcid Image ;   Brianna M White2 Author Orcid Image ;   Robert L Davis2 Author Orcid Image ;   Robert A Bednarczyk3 Author Orcid Image ;   Arash Shaban-Nejad2 Author Orcid Image
Article Authors Cited by (26) Tweetations (7) Metrics

Journals

  1. Olusanya O, White B, Malik F, Hester K, Davis R, Bednarczyk R, Shaban-Nejad A, Fischer F. Healthcare professionals’ perceptions and recommendations regarding adolescent vaccinations in Georgia and Tennessee during the COVID-19 pandemic: A qualitative research. PLOS ONE 2022;17(11):e0277748 View
  2. Catelli R, Pelosi S, Comito C, Pizzuti C, Esposito M. Lexicon-based sentiment analysis to detect opinions and attitude towards COVID-19 vaccines on Twitter in Italy. Computers in Biology and Medicine 2023;158:106876 View
  3. Wang A, Dara R, Yousefinaghani S, Maier E, Sharif S. A Review of Social Media Data Utilization for the Prediction of Disease Outbreaks and Understanding Public Perception. Big Data and Cognitive Computing 2023;7(2):72 View
  4. White B, Melton C, Zareie P, Davis R, Bednarczyk R, Shaban-Nejad A. Exploring celebrity influence on public attitude towards the COVID-19 pandemic: social media shared sentiment analysis. BMJ Health & Care Informatics 2023;30(1):e100665 View
  5. García-Rudolph A, Sanchez-Pinsach D, Frey D, Opisso E, Cisek K, Kelleher J. Know an Emotion by the Company It Keeps: Word Embeddings from Reddit/Coronavirus. Applied Sciences 2023;13(11):6713 View
  6. Franceschi J, Pareschi L, Bellodi E, Gavanelli M, Bresadola M, Vellucci P. Modeling opinion polarization on social media: Application to Covid-19 vaccination hesitancy in Italy. PLOS ONE 2023;18(10):e0291993 View
  7. Wermuth M, Sambre P. The terminological impact of pandemics. Terminology. International Journal of Theoretical and Applied Issues in Specialized Communication 2023;29(2):169 View
  8. Shah H, Househ M. Mapping loneliness through social intelligence analysis: a step towards creating global loneliness map. BMJ Health & Care Informatics 2023;30(1):e100728 View
  9. Aldosery A, Carruthers R, Kay K, Cave C, Reynolds P, Kostkova P. Enhancing public health response: a framework for topics and sentiment analysis of COVID-19 in the UK using Twitter and the embedded topic model. Frontiers in Public Health 2024;12 View
  10. Li Z, Zou Z. Punctuation and lexicon aid representation: A hybrid model for short text sentiment analysis on social media platform. Journal of King Saud University - Computer and Information Sciences 2024;36(3):102010 View
  11. Riva M, Parigi T, Ungaro F, Massimino L. Hugging Face's impact on medical applications of artificial intelligence. Computational and Structural Biotechnology Reports 2024;1:100003 View
  12. Bottacin W, Luquetta A, Gomes-Jr L, de Souza T, Reis W, Melchiors A. Sentiment analysis in medication adherence: using ruled-based and artificial intelligence-driven algorithms to understand patient medication experiences. International Journal of Clinical Pharmacy 2025;47(4):970 View
  13. White B, Prasad R, Olusanya O, Singh N, Shaban-Nejad A. Harnessing the Implementation Potential of Digital Vaccination Certificates (DVCs) on Global Scale. Procedia Computer Science 2024;251:454 View
  14. Parveen S, Pereira A, Garzon-Orjuela N, McHugh P, Surendran A, Vornhagen H, Vellinga A. COVID-19 Public Health Communication on X (Formerly Twitter): Cross-Sectional Study of Message Type, Sentiment, and Source. JMIR Formative Research 2025;9:e59687 View
  15. Saito R, Tsugawa S. Understanding Citizens’ Response to Social Activities on Twitter in US Metropolises During the COVID-19 Recovery Phase Using a Fine-Tuned Large Language Model: Application of AI. Journal of Medical Internet Research 2025;27:e63824 View
  16. Liu J, Niu Q, Nagai-Tanima M, Aoyama T. Understanding Human Papillomavirus Vaccination Hesitancy in Japan Using Social Media: Content Analysis. Journal of Medical Internet Research 2025;27:e68881 View
  17. White C, Luttman S, Avery E. Public information officers’ use of social media monitoring: An updated analysis of current practice. Public Relations Review 2025;51(1):102539 View
  18. Alafari F, Driss M, Cherif A. Advances in natural language processing for healthcare: A comprehensive review of techniques, applications, and future directions. Computer Science Review 2025;56:100725 View
  19. Shah H, Househ M. Understanding Loneliness Through Analysis of Twitter and Reddit Data: Comparative Study. Interactive Journal of Medical Research 2025;14:e49464 View
  20. Hora R, Ray A, Kumari A, Mehra R, Kaur A, F Quadri S, Ray B, Singh Koshal S, Kumar Singh S, Sultana A, Deb Roy A. Digital Media Coverage of Respiratory Syncytial Virus-Related News in India: Mixed Methods Content Analysis of Disease Burden and Intervention. JMIR Formative Research 2025;9:e70322 View
  21. Chen H, Alfred M, Cohen E. Efficient Detection of Stigmatizing Language in Electronic Health Records via In-Context Learning: Comparative Analysis and Validation Study. JMIR Medical Informatics 2025;13:e68955 View
  22. Shafiya S, Wani M, Jabin S, ELAffendi M, Jahiruddin . CoViNAR: a context-aware social media dataset for pandemic severity level prediction and analysis. Frontiers in Artificial Intelligence 2025;8 View
  23. An M, Kim M, Kim J, Chang S, Lee D, Park R, Rafi H. Public perception and changing attitudes toward antidepressants over a decade in social media: Lessons learned from online discussion using artificial intelligence. PLOS One 2025;20(9):e0318464 View

Books/Policy Documents

  1. Shaban-Nejad A, Michalowski M, Bianco S. Artificial Intelligence for Personalized Medicine. View
  2. Anoop V, Thekkiniath J, Govindarajan U. Multi-disciplinary Trends in Artificial Intelligence. View
  3. Ghahramani A, Prokofieva M, de Courten M. Health Information Science. View