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Citing this Article

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Published on 09.07.18 in Vol 20, No 7 (2018): July

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

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

Jingcheng Du, Lu Tang, Yang Xiang, Degui Zhi, Jun Xu, Hsing-Yi Song, Cui Tao

J Med Internet Res 2018 (Jul 09); 20(7):e236 

According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.9413):

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

  1. Fagherazzi G, Goetzinger C, Rashid MA, Aguayo GA, Huiart L. Digital Health Strategies to Fight COVID-19 Worldwide: Challenges, Recommendations, and a Call for Papers. Journal of Medical Internet Research 2020;22(6):e19284
    CrossRef
  2. Gupta A, Katarya R. Social media based surveillance systems for healthcare using machine learning: A systematic review. Journal of Biomedical Informatics 2020;108:103500
    CrossRef
  3. Chang Y, Chiang W, Wang W, Lin C, Hung L, Tsai Y, Suen J, Chen Y. Google Trends-based non-English language query data and epidemic diseases: a cross-sectional study of the popular search behaviour in Taiwan. BMJ Open 2020;10(7):e034156
    CrossRef
  4. Zhao Y, Guo Y, He X, Wu Y, Yang X, Prosperi M, Jin Y, Bian J. Assessing mental health signals among sexual and gender minorities using Twitter data. Health Informatics Journal 2020;26(2):765
    CrossRef
  5. Shah Z, Surian D, Dyda A, Coiera E, Mandl KD, Dunn AG. Automatically Appraising the Credibility of Vaccine-Related Web Pages Shared on Social Media: A Twitter Surveillance Study. Journal of Medical Internet Research 2019;21(11):e14007
    CrossRef
  6. Mavragani A, Ochoa G. Google Trends in Infodemiology and Infoveillance: Methodology Framework. JMIR Public Health and Surveillance 2019;5(2):e13439
    CrossRef
  7. Amith M, Cohen T, Cunningham R, Savas LS, Smith N, Cuccaro P, Gabay E, Boom J, Schvaneveldt R, Tao C. Mining HPV Vaccine Knowledge Structures of Young Adults From Reddit Using Distributional Semantics and Pathfinder Networks. Cancer Control 2020;27(1):107327481989144
    CrossRef
  8. . Tracking COVID-19 in Europe: Infodemiology Approach. JMIR Public Health and Surveillance 2020;6(2):e18941
    CrossRef
  9. Zhai Y, Yao Y, Guan Q, Liang X, Li X, Pan Y, Yue H, Yuan Z, Zhou J. Simulating urban land use change by integrating a convolutional neural network with vector-based cellular automata. International Journal of Geographical Information Science 2020;34(7):1475
    CrossRef
  10. . Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206
    CrossRef
  11. Rashid MT, Wang D. CovidSens: a vision on reliable social sensing for COVID-19. Artificial Intelligence Review 2021;54(1):1
    CrossRef
  12. Meadows CW, Meadows CZ, Tang L, Liu W. Unraveling Public Health Crises Across Stages: Understanding Twitter Emotions and Message Types During the California Measles Outbreak. Communication Studies 2019;70(4):453
    CrossRef
  13. Du J, Chen Q, Peng Y, Xiang Y, Tao C, Lu Z. ML-Net: multi-label classification of biomedical texts with deep neural networks. Journal of the American Medical Informatics Association 2019;26(11):1279
    CrossRef
  14. Lili D, Lei S, Gang X, Patnaik S. Public opinion analysis of complex network information of local similarity clustering based on intelligent fuzzy system. Journal of Intelligent & Fuzzy Systems 2020;39(2):1693
    CrossRef
  15. Du J, Luo C, Shegog R, Bian J, Cunningham RM, Boom JA, Poland GA, Chen Y, Tao C. Use of Deep Learning to Analyze Social Media Discussions About the Human Papillomavirus Vaccine. JAMA Network Open 2020;3(11):e2022025
    CrossRef
  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
    CrossRef
  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
    CrossRef
  18. Mavragani A, Gkillas K. COVID-19 predictability in the United States using Google Trends time series. Scientific Reports 2020;10(1)
    CrossRef
  19. Ibrahim MA, Ghani Khan MU, Mehmood F, Asim MN, Mahmood W. GHS-NET a generic hybridized shallow neural network for multi-label biomedical text classification. Journal of Biomedical Informatics 2021;116:103699
    CrossRef
  20. Karafillakis E, Martin S, Simas C, Olsson K, Takacs J, Dada S, Larson HJ. Methods for Social Media Monitoring Related to Vaccination: Systematic Scoping Review. JMIR Public Health and Surveillance 2021;7(2):e17149
    CrossRef
  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
    CrossRef
  22. Tang L, Liu W, Thomas B, Tran HTN, 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
    CrossRef
  23. Bali AO, Halbusi HA, Ahmad AR, Lee KY, Lavorgna L. Public engagement in government officials’ posts on social media during coronavirus lockdown. PLOS ONE 2023;18(1):e0280889
    CrossRef
  24. Lian AT, 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
    CrossRef
  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
    CrossRef
  26. Teague SJ, Shatte ABR, Weller E, Fuller-Tyszkiewicz M, Hutchinson DM. Methods and Applications of Social Media Monitoring of Mental Health During Disasters: Scoping Review. JMIR Mental Health 2022;9(2):e33058
    CrossRef
  27. dos Santos BS, Steiner MTA, Lima RHP. Proposal of a method to classify female smokers based on data mining techniques. Computers & Industrial Engineering 2022;170:108363
    CrossRef
  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
    CrossRef
  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
    CrossRef
  30. Doll MK, Correira JW. Revisiting the 2014-15 Disneyland measles outbreak and its influence on pediatric vaccinations. Human Vaccines & Immunotherapeutics 2021;17(11):4210
    CrossRef
  31. Sitaula C, Basnet A, Mainali A, Shahi TB, G TR. Deep Learning-Based Methods for Sentiment Analysis on Nepali COVID-19-Related Tweets. Computational Intelligence and Neuroscience 2021;2021:1
    CrossRef
  32. Porcu G, Chen YX, Bonaugurio AS, 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
    CrossRef
  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
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/jmir.9413):

  1. Slavescu RR, Pop F, Slavescu KC. 7th International Conference on Advancements of Medicine and Health Care through Technology. 2022. Chapter 29:259
    CrossRef
  2. . Spatially Explicit Hyperparameter Optimization for Neural Networks. 2021. Chapter 6:81
    CrossRef
  3. Rakesh B, Nayak S. Deep Learning in Personalized Healthcare and Decision Support. 2023. :215
    CrossRef
  4. Osop H, Wong JY, Lwin SW, Lee CS. Leveraging Generative Intelligence in Digital Libraries: Towards Human-Machine Collaboration. 2023. Chapter 15:167
    CrossRef