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

Infodemiology and Infoveillance (1349) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1641) Natural Language Processing (692) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041) Machine Learning (1465)

Published on in Vol 20, No 7 (2018): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/9413, first published .
Public Perception Analysis of Tweets During the 2015 Measles Outbreak: Comparative Study Using Convolutional Neural Network Models

Public Perception Analysis of Tweets During the 2015 Measles Outbreak: Comparative Study Using Convolutional Neural Network Models

Public Perception Analysis of Tweets During the 2015 Measles Outbreak: Comparative Study Using Convolutional Neural Network Models

Authors of this article:

Jingcheng Du1 Author Orcid Image ;   Lu Tang2 Author Orcid Image ;   Yang Xiang1 Author Orcid Image ;   Degui Zhi1 Author Orcid Image ;   Jun Xu1 Author Orcid Image ;   Hsing-Yi Song1 Author Orcid Image ;   Cui Tao1 Author Orcid Image
Article Authors Cited by (41) Tweetations (15) Metrics

Journals

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  16. Tang L, Zou W. Health Information Consumption under COVID-19 Lockdown: An Interview Study of Residents of Hubei Province, China. Health Communication 2021;36(1):74 View
  17. Shen L, Yao R, Zhang W, Evans R, Cao G, Zhang Z. Emotional Attitudes of Chinese Citizens on Social Distancing During the COVID-19 Outbreak: Analysis of Social Media Data. JMIR Medical Informatics 2021;9(3):e27079 View
  18. Mavragani A, Gkillas K. COVID-19 predictability in the United States using Google Trends time series. Scientific Reports 2020;10(1) View
  19. Ibrahim M, Ghani Khan M, Mehmood F, Asim M, Mahmood W. GHS-NET a generic hybridized shallow neural network for multi-label biomedical text classification. Journal of Biomedical Informatics 2021;116:103699 View
  20. Karafillakis E, Martin S, Simas C, Olsson K, Takacs J, Dada S, Larson H. Methods for Social Media Monitoring Related to Vaccination: Systematic Scoping Review. JMIR Public Health and Surveillance 2021;7(2):e17149 View
  21. Bonnevie E, Gallegos-Jeffrey A, Goldbarg J, Byrd B, Smyser J. Quantifying the rise of vaccine opposition on Twitter during the COVID-19 pandemic. Journal of Communication in Healthcare 2021;14(1):12 View
  22. Tang L, Liu W, Thomas B, Tran H, Zou W, Zhang X, Zhi D. Texas Public Agencies’ Tweets and Public Engagement During the COVID-19 Pandemic: Natural Language Processing Approach. JMIR Public Health and Surveillance 2021;7(4):e26720 View
  23. Bali A, Halbusi H, Ahmad A, Lee K, Lavorgna L. Public engagement in government officials’ posts on social media during coronavirus lockdown. PLOS ONE 2023;18(1):e0280889 View
  24. Lian A, Du J, Tang L. Using a Machine Learning Approach to Monitor COVID-19 Vaccine Adverse Events (VAE) from Twitter Data. Vaccines 2022;10(1):103 View
  25. Crescioli G, Bonaiuti R, Corradetti R, Mannaioni G, Vannacci A, Lombardi N. Pharmacovigilance and Pharmacoepidemiology as a Guarantee of Patient Safety: The Role of the Clinical Pharmacologist. Journal of Clinical Medicine 2022;11(12):3552 View
  26. Teague S, Shatte A, Weller E, Fuller-Tyszkiewicz M, Hutchinson D. Methods and Applications of Social Media Monitoring of Mental Health During Disasters: Scoping Review. JMIR Mental Health 2022;9(2):e33058 View
  27. dos Santos B, Steiner M, Lima R. Proposal of a method to classify female smokers based on data mining techniques. Computers & Industrial Engineering 2022;170:108363 View
  28. Amin S, Irfan Uddin M, Ali Zeb M, Abdulsalam Alarood A, Mahmoud M, H. Alkinani M. Detecting Information on the Spread of Dengue on Twitter Using Artificial Neural Networks. Computers, Materials & Continua 2021;67(1):1317 View
  29. Gour A, Aggarwal S, Kumar S. Lending ears to unheard voices: An empirical analysis of user‐generated content on social media. Production and Operations Management 2022;31(6):2457 View
  30. Doll M, Correira J. Revisiting the 2014-15 Disneyland measles outbreak and its influence on pediatric vaccinations. Human Vaccines & Immunotherapeutics 2021;17(11):4210 View
  31. Sitaula C, Basnet A, Mainali A, Shahi T, G T. Deep Learning‐Based Methods for Sentiment Analysis on Nepali COVID‐19‐Related Tweets. Computational Intelligence and Neuroscience 2021;2021(1) View
  32. Porcu G, Chen Y, Bonaugurio A, Villa S, Riva L, Messina V, Bagarella G, Maistrello M, Leoni O, Cereda D, Matone F, Gori A, Corrao G. Web-based surveillance of respiratory infection outbreaks: retrospective analysis of Italian COVID-19 epidemic waves using Google Trends. Frontiers in Public Health 2023;11 View
  33. Zou W, Tang L, Zhou M, Zhang X. Self-disclosure and received social support among women experiencing infertility on reddit: A natural language processing approach. Computers in Human Behavior 2024;154:108159 View

Books/Policy Documents

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