Published on 24.10.13 in Vol 15, No 10 (2013): October
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)
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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
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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
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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
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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
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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
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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
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Gurajala S, Dhaniyala S, Matthews JN. Understanding Public Response to Air Quality Using Tweet Analysis. Social Media + Society 2019;5(3):205630511986765
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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
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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
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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
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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
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Zeraatkar K, Ahmadi M. Trends of infodemiology studies: a scoping review. Health Information & Libraries Journal 2018;35(2):91
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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
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Lardon J, Bellet F, Aboukhamis R, Asfari H, Souvignet J, Jaulent M, Beyens M, Lillo-LeLouët A, Bousquet C. Evaluating Twitter as a complementary data source for pharmacovigilance. Expert Opinion on Drug Safety 2018;17(8):763
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Zhang Y, Bambrick H, Mengersen K, Tong S, Feng L, Zhang L, Liu G, Xu A, Hu W. Using big data to predict pertussis infections in Jinan city, China: a time series analysis. International Journal of Biometeorology 2020;64(1):95
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Broniatowski DA, Dredze M, Paul MJ, Dugas A. Using Social Media to Perform Local Influenza Surveillance in an Inner-City Hospital: A Retrospective Observational Study. JMIR Public Health and Surveillance 2015;1(1):e5
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. Trace of pace, place, and space in personal relationships: The chronogeometrics of studying relationships at scale. Personal Relationships 2019;26(2):184
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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
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Barros JM, Duggan J, Rebholz-Schuhmann D. The Application of Internet-Based Sources for Public Health Surveillance (Infoveillance): Systematic Review. Journal of Medical Internet Research 2020;22(3):e13680
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Tulloch JS, Vivancos R, Christley RM, Radford AD, Warner JC. Mapping tweets to a known disease epidemiology; a case study of Lyme disease in the United Kingdom and Republic of Ireland. Journal of Biomedical Informatics 2019;100:100060
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. Twitter and Health Science Research. Western Journal of Nursing Research 2015;37(10):1269
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Schwab-Reese LM, Hovdestad W, Tonmyr L, Fluke J. The potential use of social media and other internet-related data and communications for child maltreatment surveillance and epidemiological research: Scoping review and recommendations. Child Abuse & Neglect 2018;85:187
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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
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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
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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)
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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
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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
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Zhang AJ, Albrecht L, Scott SD. Using Twitter for Data Collection With Health-Care Consumers. International Journal of Qualitative Methods 2018;17(1):160940691775078
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. Toward A Model of Meme Diffusion (M3D). Communication Theory 2014;24(3):311
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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
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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
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Gao Y, Wang S, Padmanabhan A, Yin J, Cao G. Mapping spatiotemporal patterns of events using social media: a case study of influenza trends. International Journal of Geographical Information Science 2018;32(3):425
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. A prospect for the geographical research of sport in the age of Big Data. Sport in Society 2020;23(1):159
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Yang J, Tsou M, Janowicz K, Clarke KC, Jankowski P. Reshaping the urban hierarchy: patterns of information diffusion on social media. Geo-spatial Information Science 2019;22(3):149
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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
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Oldroyd RA, Morris MA, Birkin M. Identifying Methods for Monitoring Foodborne Illness: Review of Existing Public Health Surveillance Techniques. JMIR Public Health and Surveillance 2018;4(2):e57
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Radin JM, Wineinger NE, Topol EJ, Steinhubl SR. Harnessing wearable device data to improve state-level real-time surveillance of influenza-like illness in the USA: a population-based study. The Lancet Digital Health 2020;2(2):e85
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Zhang Y, Bambrick H, Mengersen K, Tong S, Hu W. Using Google Trends and ambient temperature to predict seasonal influenza outbreaks. Environment International 2018;117:284
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Cuomo RE, Cai M, Shah N, Li J, Chen W, Obradovich N, Mackey TK. Characterising communities impacted by the 2015 Indiana HIV outbreak: A big data analysis of social media messages associated with HIV and substance abuse. Drug and Alcohol Review 2020;39(7):908
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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
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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 2018;11(5):451
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Gabarron E, Rivera-Romero O, Miron-Shatz T, Grainger R, Denecke K. Role of Participatory Health Informatics in Detecting and Managing Pandemics: Literature Review. Yearbook of Medical Informatics 2021;30(01):200
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Kumarasamy AKT, Asamoah DA, Sharda R. Non-Communicable Diseases and Social Media: A Heart Disease Symptoms Application. Journal of Information & Knowledge Management 2021;20(04)
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Ji H, Wang J, Meng B, Cao Z, Yang T, Zhi G, Chen S, Wang S, Zhang J. Research on adaption to air pollution in Chinese cities: Evidence from social media-based health sensing. Environmental Research 2022;210:112762
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Chen M, An L, Li G, Yu C. Severity assessment and the early warning mechanism of public events based on the comparison of microblogging characteristics. Information Technology & People 2023;36(6):2543
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Jabalameli S, Xu Y, Shetty S. Spatial and sentiment analysis of public opinion toward COVID-19 pandemic using twitter data: At the early stage of vaccination. International Journal of Disaster Risk Reduction 2022;80:103204
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Li C, Zhao J, Yin J, Chi G. Park access affects physical activity: new evidence from geolocated Twitter data analysis. Journal of Urban Design 2023;28(3):316
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Zhang X, Mu L, Zhang D, Mao Y, Shi L, Rajbhandari-Thapa J, Chen Z, Li Y, Pagán JA. Geographical and Temporal Analysis of Tweets Related to COVID-19 and Cardiovascular Disease in the US. Annals of GIS 2022;28(4):491
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. MonkeyPox2022Tweets: A Large-Scale Twitter Dataset on the 2022 Monkeypox Outbreak, Findings from Analysis of Tweets, and Open Research Questions. Infectious Disease Reports 2022;14(6):855
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Hammond A, Kim JJ, Sadler H, Vandemaele K. Influenza surveillance systems using traditional and alternative sources of data: A scoping review. Influenza and Other Respiratory Viruses 2022;16(6):965
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Jabalameli S, Xu Y, Shetty S. The Spatial and Sentiment Analysis of Public Opinion Toward Covid-19 Pandemic Using Twitter Data: At the Early Stage of Vaccination. SSRN Electronic Journal 2022;
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Li W, Haunert J, Knechtel J, Zhu J, Zhu Q, Dehbi Y. Social media insights on public perception and sentiment during and after disasters: The European floods in 2021 as a case study. Transactions in GIS 2023;27(6):1766
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Park J, Tsou M, Nara A, Cassels S, Dodge S. Developing a social sensing index for monitoring place-oriented mental health issues using social media (twitter) data. Urban Informatics 2024;3(1)
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According to Crossref, the following books are citing this article (DOI 10.2196/jmir.2705):
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Samaras L, García-Barriocanal E, Sicilia M. Innovation in Health Informatics. 2020. :39
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Spitzberg BH, Tsou M, Jung C. The Handbook of Applied Communication Research. 2020. :163
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Nara A, Tsou M, Yang J, Huang C. Human Dynamics Research in Smart and Connected Communities. 2018. Chapter 12:223
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Xiong Y, He Y, Huang H, Yu C, Jing X. Signal and Information Processing, Networking and Computers. 2020. Chapter 10:78
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Yang J, Tsou M, Spitzberg B, An L, Gawron JM, Gupta D. CyberGIS for Geospatial Discovery and Innovation. 2019. Chapter 5:71
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Spitzberg BH, Tsou M, Gawron M. Communicating Science in Times of Crisis. 2021. :262
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Martinez LS, Tsou M, Spitzberg BH. Empowering Human Dynamics Research with Social Media and Geospatial Data Analytics. 2021. Chapter 11:203
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Yin Z, Ni C, Fabbri D, Rosenbloom ST, Malin B. Personal Health Informatics. 2022. Chapter 12:247
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