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Citing this Article

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Published on 20.10.16 in Vol 2, No 2 (2016): Jul-Dec

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

Works citing "Evaluating Google, Twitter, and Wikipedia as Tools for Influenza Surveillance Using Bayesian Change Point Analysis: A Comparative Analysis"

According to Crossref, the following articles are citing this article (DOI 10.2196/publichealth.5901):

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

  1. Smith DA, Triberti S. Situating Wikipedia as a health information resource in various contexts: A scoping review. PLOS ONE 2020;15(2):e0228786
    CrossRef
  2. Barros JM, Duggan J, Rebholz-Schuhmann D. Internet-Based Sources of Health Information: A Systematic Literature Review (Preprint). Journal of Medical Internet Research 2019;
    CrossRef
  3. Safarishahrbijari A, Osgood ND. Social Media Surveillance for Outbreak Projection via Transmission Models: Longitudinal Observational Study. JMIR Public Health and Surveillance 2019;5(2):e11615
    CrossRef
  4. Gao J, Zhang Y, Zhou T. Computational socioeconomics. Physics Reports 2019;817:1
    CrossRef
  5. Kim M, Yune S, Chang S, Jung Y, Sa SO, Han HW. The Fever Coach Mobile App for Participatory Influenza Surveillance in Children: Usability Study. JMIR mHealth and uHealth 2019;7(10):e14276
    CrossRef
  6. Soliman M, Lyubchich V, Gel YR. Complementing the power of deep learning with statistical model fusion: Probabilistic forecasting of influenza in Dallas County, Texas, USA. Epidemics 2019;28:100345
    CrossRef
  7. Yang C, Chen R, Chou W, Lee Y, Lo Y. An Integrated Influenza Surveillance Framework Based on National Influenza-Like Illness Incidence and Multiple Hospital Electronic Medical Records for Early Prediction of Influenza Epidemics: Design and Evaluation. Journal of Medical Internet Research 2019;21(2):e12341
    CrossRef
  8. Ferland R, Froda S. A statistical tool for comparing seasonal ILI surveillance data. Scientific Reports 2019;9(1)
    CrossRef
  9. Sarker A, Gonzalez-Hernandez G, Ruan Y, Perrone J. Machine Learning and Natural Language Processing for Geolocation-Centric Monitoring and Characterization of Opioid-Related Social Media Chatter. JAMA Network Open 2019;2(11):e1914672
    CrossRef
  10. Wakamiya S, Matsune S, Okubo K, Aramaki E. Causal Relationships Among Pollen Counts, Tweet Numbers, and Patient Numbers for Seasonal Allergic Rhinitis Surveillance: Retrospective Analysis. Journal of Medical Internet Research 2019;21(2):e10450
    CrossRef
  11. Riley WT, Oh A, Aklin WM, Wolff-Hughes DL. National Institutes of Health Support of Digital Health Behavior Research. Health Education & Behavior 2019;46(2_suppl):12S
    CrossRef
  12. Astill J, Dara RA, Fraser EDG, Sharif S. Detecting and Predicting Emerging Disease in Poultry With the Implementation of New Technologies and Big Data: A Focus on Avian Influenza Virus. Frontiers in Veterinary Science 2018;5
    CrossRef
  13. Zeraatkar K, Ahmadi M. Trends of infodemiology studies: a scoping review. Health Information & Libraries Journal 2018;35(2):91
    CrossRef
  14. Dembek ZF, Chekol T, Wu A. Best practice assessment of disease modelling for infectious disease outbreaks. Epidemiology and Infection 2018;146(10):1207
    CrossRef
  15. Martinho T. Researching Culture through Big Data: Computational Engineering and the Human and Social Sciences. Social Sciences 2018;7(12):264
    CrossRef
  16. Kolff CA, Scott VP, Stockwell MS. The use of technology to promote vaccination: A social ecological model based framework. Human Vaccines & Immunotherapeutics 2018;14(7):1636
    CrossRef
  17. Mougin F, Auber D, Bourqui R, Diallo G, Dutour I, Jouhet V, Thiessard F, Thiébaut R, Thébault P. Visualizing omics and clinical data: Which challenges for dealing with their variety?. Methods 2018;132:3
    CrossRef
  18. Chen S, Xu Q, Buchenberger J, Bagavathi A, Fair G, Shaikh S, Krishnan S. Dynamics of Health Agency Response and Public Engagement in Public Health Emergency: A Case Study of CDC Tweeting Patterns During the 2016 Zika Epidemic. JMIR Public Health and Surveillance 2018;4(4):e10827
    CrossRef
  19. Sarker A, Chandrashekar P, Magge A, Cai H, Klein A, Gonzalez G. Discovering Cohorts of Pregnant Women From Social Media for Safety Surveillance and Analysis. Journal of Medical Internet Research 2017;19(10):e361
    CrossRef
  20. Paul MJ, Dredze M. Social Monitoring for Public Health. Synthesis Lectures on Information Concepts, Retrieval, and Services 2017;9(5):1
    CrossRef
  21. Brownstein JS, Chu S, Marathe A, Marathe MV, Nguyen AT, Paolotti D, Perra N, Perrotta D, Santillana M, Swarup S, Tizzoni M, Vespignani A, Vullikanti AKS, Wilson ML, Zhang Q. Combining Participatory Influenza Surveillance with Modeling and Forecasting: Three Alternative Approaches. JMIR Public Health and Surveillance 2017;3(4):e83
    CrossRef
  22. Kagashe I, Yan Z, Suheryani I. Enhancing Seasonal Influenza Surveillance: Topic Analysis of Widely Used Medicinal Drugs Using Twitter Data. Journal of Medical Internet Research 2017;19(9):e315
    CrossRef
  23. Borron SW, Watts SH, Tull J, Baeza S, Diebold S, Barrow A. Intentional Misuse and Abuse of Loperamide: A New Look at a Drug with “Low Abuse Potential”. The Journal of Emergency Medicine 2017;53(1):73
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/publichealth.5901)

:
  1. Samaras L, García-Barriocanal E, Sicilia M. Innovation in Health Informatics. 2020. :39
    CrossRef
  2. da Silva DA, Goncalves GS, dos Santos SC, Pugliese VU, Navas J, de Barros Santana RM, Queiroz FS, Dias LAV, da Cunha AM, Tasinaffo PM. Information Technology – New Generations. 2018. Chapter 34:233
    CrossRef