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Journal of Medical Internet Research

Citing this Article

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Published on 24.10.13 in Vol 15, No 10 (2013): October

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

Works citing "The Complex Relationship of Realspace Events and Messages in Cyberspace: Case Study of Influenza and Pertussis Using Tweets"

According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.2705):

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

  1. Issa E, Tsou M, Nara A, Spitzberg B. Understanding the spatio-temporal characteristics of Twitter data with geotagged and non-geotagged content: two case studies with the topic of flu and Ted (movie). Annals of GIS 2017;23(3):219
    CrossRef
  2. Yan S, Chughtai A, Macintyre C. Utility and potential of rapid epidemic intelligence from internet-based sources. International Journal of Infectious Diseases 2017;63:77
    CrossRef
  3. SPRECO A, ERIKSSON O, DAHLSTRÖM , TIMPKA T. Influenza detection and prediction algorithms: comparative accuracy trial in Östergötland county, Sweden, 2008–2012. Epidemiology and Infection 2017;145(10):2166
    CrossRef
  4. Hartley DM, Giannini CM, Wilson S, Frieder O, Margolis PA, Kotagal UR, White DL, Connelly BL, Wheeler DS, Tadesse DG, Macaluso M, Nishiura H. Coughing, sneezing, and aching online: Twitter and the volume of influenza-like illness in a pediatric hospital. PLOS ONE 2017;12(7):e0182008
    CrossRef
  5. Nguyen QC, McCullough M, Meng H, Paul D, Li D, Kath S, Loomis G, Nsoesie EO, Wen M, Smith KR, Li F. Geotagged US Tweets as Predictors of County-Level Health Outcomes, 2015–2016. American Journal of Public Health 2017;107(11):1776
    CrossRef
  6. Han SY, Tsou M, Clarke KC. Revisiting the death of geography in the era of Big Data: the friction of distance in cyberspace and real space. International Journal of Digital Earth 2017;:1
    CrossRef
  7. Kim I, Feng C, Wang Y, Spitzberg BH, Tsou M. Exploratory Spatiotemporal Analysis in Risk Communication during the MERS Outbreak in South Korea. The Professional Geographer 2017;69(4):629
    CrossRef
  8. Wang Y, Fu X, Jiang W, Wang T, Tsou M, Ye X. Inferring urban air quality based on social media. Computers, Environment and Urban Systems 2017;66:110
    CrossRef
  9. Kim K, Kojima I, Ogawa H. Discovery of local topics by using latent spatio-temporal relationships in geo-social media. International Journal of Geographical Information Science 2016;30(9):1899
    CrossRef
  10. Seidenberg AB, Pagoto SL, Vickey TA, Linos E, Wehner MR, Costa RD, Geller AC. Tanning bed burns reported on Twitter: over 15,000 in 2013. Translational Behavioral Medicine 2016;6(2):271
    CrossRef
  11. An L, Tsou M, Spitzberg BH, Gupta DK, Gawron JM. Latent trajectory models for space-time analysis: An application in deciphering spatial panel data. Geographical Analysis 2016;48(3):314
    CrossRef
  12. Allen C, Tsou M, Aslam A, Nagel A, Gawron J, Ebrahimi M. Applying GIS and Machine Learning Methods to Twitter Data for Multiscale Surveillance of Influenza. PLOS ONE 2016;11(7):e0157734
    CrossRef
  13. Yang J, Tsou M, Jung C, Allen C, Spitzberg BH, Gawron JM, Han S. Social media analytics and research testbed (SMART): Exploring spatiotemporal patterns of human dynamics with geo-targeted social media messages. Big Data & Society 2016;3(1):205395171665291
    CrossRef
  14. Padrez KA, Ungar L, Schwartz HA, Smith RJ, Hill S, Antanavicius T, Brown DM, Crutchley P, Asch DA, Merchant RM. Linking social media and medical record data: a study of adults presenting to an academic, urban emergency department. BMJ Quality & Safety 2016;25(6):414
    CrossRef
  15. Han SY, Tsou M, Clarke KC, Hernandez Montoya AR. Do Global Cities Enable Global Views? Using Twitter to Quantify the Level of Geographical Awareness of U.S. Cities. PLOS ONE 2015;10(7):e0132464
    CrossRef
  16. Wang Y, Wang T, Ye X, Zhu J, Lee J. Using Social Media for Emergency Response and Urban Sustainability: A Case Study of the 2012 Beijing Rainstorm. Sustainability 2015;8(1):25
    CrossRef
  17. Finfgeld-Connett D. Twitter and Health Science Research. Western Journal of Nursing Research 2015;37(10):1269
    CrossRef
  18. Mok K, Jorm AF, Pirkis J. Suicide-related Internet use: A review. Australian & New Zealand Journal of Psychiatry 2015;49(8):697
    CrossRef
  19. Cao G, Wang S, Hwang M, Padmanabhan A, Zhang Z, Soltani K. A scalable framework for spatiotemporal analysis of location-based social media data. Computers, Environment and Urban Systems 2015;51:70
    CrossRef
  20. Jiang W, Wang Y, Tsou M, Fu X, Amaral LAN. Using Social Media to Detect Outdoor Air Pollution and Monitor Air Quality Index (AQI): A Geo-Targeted Spatiotemporal Analysis Framework with Sina Weibo (Chinese Twitter). PLOS ONE 2015;10(10):e0141185
    CrossRef
  21. Yin Z, Fabbri D, Rosenbloom ST, Malin B. A Scalable Framework to Detect Personal Health Mentions on Twitter. Journal of Medical Internet Research 2015;17(6):e138
    CrossRef
  22. Generous N, Fairchild G, Deshpande A, Del Valle SY, Priedhorsky R, Salathé M. Global Disease Monitoring and Forecasting with Wikipedia. PLoS Computational Biology 2014;10(11):e1003892
    CrossRef
  23. Aslam AA, Tsou M, Spitzberg BH, An L, Gawron JM, Gupta DK, Peddecord KM, Nagel AC, Allen C, Yang J, Lindsay S. The Reliability of Tweets as a Supplementary Method of Seasonal Influenza Surveillance. Journal of Medical Internet Research 2014;16(11):e250
    CrossRef
  24. Spitzberg BH. Toward A Model of Meme Diffusion (M3D). Communication Theory 2014;24(3):311
    CrossRef
  25. Nagar R, Yuan Q, Freifeld CC, Santillana M, Nojima A, Chunara R, Brownstein JS. A Case Study of the New York City 2012-2013 Influenza Season With Daily Geocoded Twitter Data From Temporal and Spatiotemporal Perspectives. Journal of Medical Internet Research 2014;16(10):e236
    CrossRef