Published on 20.10.14 in Vol 16, No 10 (2014): October
Works citing "A Case Study of the New York City 2012-2013 Influenza Season With Daily Geocoded Twitter Data From Temporal and Spatiotemporal Perspectives"
According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.3416):
(note that this is only a small subset of citations)
- 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):e13680CrossRef
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- Bowen DA, Wang J, Holland K, Bartholow B, Sumner SA. Conversational topics of social media messages associated with state-level mental distress rates. Journal of Mental Health 2020;29(2):234CrossRef
- Murayama T, Shimizu N, Fujita S, Wakamiya S, Aramaki E, Wen T. Robust two-stage influenza prediction model considering regular and irregular trends. PLOS ONE 2020;15(5):e0233126CrossRef
- Samuel J, Ali GGMN, Rahman MM, Esawi E, Samuel Y. COVID-19 Public Sentiment Insights and Machine Learning for Tweets Classification. Information 2020;11(6):314CrossRef
- Cumbraos-Sánchez MJ, Hermoso R, Iñiguez D, Paño-Pardo JR, Allende Bandres M, Latorre Martinez MP. Qualitative and quantitative evaluation of the use of Twitter as a tool of antimicrobial stewardship. International Journal of Medical Informatics 2019;131:103955CrossRef
- Șerban O, Thapen N, Maginnis B, Hankin C, Foot V. Real-time processing of social media with SENTINEL: A syndromic surveillance system incorporating deep learning for health classification. Information Processing & Management 2019;56(3):1166CrossRef
- Puspitasari I, Firdauzy A. Characterizing Consumer Behavior in Leveraging Social Media for E-Patient and Health-Related Activities. International Journal of Environmental Research and Public Health 2019;16(18):3348CrossRef
- 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: X 2019;4:100060CrossRef
- Lee M, Jung I. Modified spatial scan statistics using a restricted likelihood ratio for ordinal outcome data. Computational Statistics & Data Analysis 2019;133:28CrossRef
- Masri S, Jia J, Li C, Zhou G, Lee M, Yan G, Wu J. Use of Twitter data to improve Zika virus surveillance in the United States during the 2016 epidemic. BMC Public Health 2019;19(1)CrossRef
- Little RJA, West BT, Boonstra PS, Hu J. Measures of the Degree of Departure from Ignorable Sample Selection. Journal of Survey Statistics and Methodology 2019;CrossRef
- Lu FS, Hou S, Baltrusaitis K, Shah M, Leskovec J, Sosic R, Hawkins J, Brownstein J, Conidi G, Gunn J, Gray J, Zink A, Santillana M. Accurate Influenza Monitoring and Forecasting Using Novel Internet Data Streams: A Case Study in the Boston Metropolis. JMIR Public Health and Surveillance 2018;4(1):e4CrossRef
- 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):e10827CrossRef
- Wakamiya S, Kawai Y, Aramaki E. Twitter-Based Influenza Detection After Flu Peak via Tweets With Indirect Information: Text Mining Study. JMIR Public Health and Surveillance 2018;4(3):e65CrossRef
- Hampson G, Towse A, Dreitlein WB, Henshall C, Pearson SD. Real-world evidence for coverage decisions: opportunities and challenges. Journal of Comparative Effectiveness Research 2018;7(12):1133CrossRef
- Stock K. Mining location from social media: A systematic review. Computers, Environment and Urban Systems 2018;71:209CrossRef
- Hu Y. Geo-text data and data-driven geospatial semantics. Geography Compass 2018;12(11):e12404CrossRef
- 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):e57CrossRef
- Barros JM, Duggan J, Rebholz-Schuhmann D. Disease mentions in airport and hospital geolocations expose dominance of news events for disease concerns. Journal of Biomedical Semantics 2018;9(1)CrossRef
- Relia K, Akbari M, Duncan D, Chunara R. Socio-spatial Self-organizing Maps. Proceedings of the ACM on Human-Computer Interaction 2018;2(CSCW):1CrossRef
- Musa I, Park H, Munkhdalai L, Ryu K. Global Research on Syndromic Surveillance from 1993 to 2017: Bibliometric Analysis and Visualization. Sustainability 2018;10(10):3414CrossRef
- Zhou L, Zhang D, Yang CC, Wang Y. Harnessing social media for health information management. Electronic Commerce Research and Applications 2018;27:139CrossRef
- Hu H, Wang H, Wang F, Langley D, Avram A, Liu M. Prediction of influenza-like illness based on the improved artificial tree algorithm and artificial neural network. Scientific Reports 2018;8(1)CrossRef
- Zeraatkar K, Ahmadi M. Trends of infodemiology studies: a scoping review. Health Information & Libraries Journal 2018;35(2):91CrossRef
- 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):e83CrossRef
- Ozdikis O, Oğuztüzün H, Karagoz P. A survey on location estimation techniques for events detected in Twitter. Knowledge and Information Systems 2017;52(2):291CrossRef
- Burke-Garcia A, Stanton CA. A tale of two tools: Reliability and feasibility of social media measurement tools examining e-cigarette twitter mentions. Informatics in Medicine Unlocked 2017;8:8CrossRef
- Geofrey A, Kipanyula MJ, Fue K, Sanga C. Understanding Strategies for Implementing Integrated Information Systems for Rabies Surveillance. International Journal of User-Driven Healthcare 2017;7(1):13CrossRef
- 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):e0182008CrossRef
- Meng H, Kath S, Li D, Nguyen QC, Giraud-Carrier C. National substance use patterns on Twitter. PLOS ONE 2017;12(11):e0187691CrossRef
- Nguyen Q, Meng H, Li D, Kath S, McCullough M, Paul D, Kanokvimankul P, Nguyen T, Li F. Social media indicators of the food environment and state health outcomes. Public Health 2017;148:120CrossRef
- Rabarison KM, Croston MA, Englar NK, Bish CL, Flynn SM, Johnson CC. Measuring Audience Engagement for Public Health Twitter Chats: Insights From #LiveFitNOLA. JMIR Public Health and Surveillance 2017;3(2):e34CrossRef
- Paul MJ, Dredze M. Social Monitoring for Public Health. Synthesis Lectures on Information Concepts, Retrieval, and Services 2017;9(5):1CrossRef
- McGough SF, Brownstein JS, Hawkins JB, Santillana M, Althouse B. Forecasting Zika Incidence in the 2016 Latin America Outbreak Combining Traditional Disease Surveillance with Search, Social Media, and News Report Data. PLOS Neglected Tropical Diseases 2017;11(1):e0005295CrossRef
- Gruebner O, Lowe SR, Sykora M, Shankardass K, Subramanian SV, Galea S, Olson DR. A novel surveillance approach for disaster mental health. PLOS ONE 2017;12(7):e0181233CrossRef
- Brown B, Smeeth L, van Staa T, Buchan I. Better care through better use of data in GP–patient partnerships. British Journal of General Practice 2017;67(655):54CrossRef
- Sharpe JD, Hopkins RS, Cook RL, Striley CW. Evaluating Google, Twitter, and Wikipedia as Tools for Influenza Surveillance Using Bayesian Change Point Analysis: A Comparative Analysis. JMIR Public Health and Surveillance 2016;2(2):e161CrossRef
- Simonsen L, Gog JR, Olson D, Viboud C. Infectious Disease Surveillance in the Big Data Era: Towards Faster and Locally Relevant Systems. Journal of Infectious Diseases 2016;214(suppl 4):S380CrossRef
- Gunn JE, Shah SN. Big data and opportunities for injury surveillance. Injury Prevention 2016;22(Suppl 1):i3CrossRef
- Gruebner O, Sykora M, Lowe SR, Shankardass K, Trinquart L, Jackson T, Subramanian SV, Galea S. Mental health surveillance after the terrorist attacks in Paris. The Lancet 2016;387(10034):2195CrossRef
- Agarwal V, Zhang L, Zhu J, Fang S, Cheng T, Hong C, Shah NH. Impact of Predicting Health Care Utilization Via Web Search Behavior: A Data-Driven Analysis. Journal of Medical Internet Research 2016;18(9):e251CrossRef
- Thapen N, Simmie D, Hankin C, Gillard J, Danforth CM. DEFENDER: Detecting and Forecasting Epidemics Using Novel Data-Analytics for Enhanced Response. PLOS ONE 2016;11(5):e0155417CrossRef
- Kunkle S, Christie G, Yach D, El-Sayed AM. The Importance of Computer Science for Public Health Training: An Opportunity and Call to Action. JMIR Public Health and Surveillance 2016;2(1):e10CrossRef
- Househ M. Communicating Ebola through social media and electronic news media outlets: A cross-sectional study. Health Informatics Journal 2016;22(3):470CrossRef
- Santillana M, Nguyen AT, Louie T, Zink A, Gray J, Sung I, Brownstein JS. Cloud-based Electronic Health Records for Real-time, Region-specific Influenza Surveillance. Scientific Reports 2016;6(1)CrossRef
- 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):205395171665291CrossRef
- Shin S, Kim T, Seo D, Sohn CH, Kim S, Ryoo SM, Lee Y, Lee JH, Kim WY, Lim KS, Olson DR. Correlation between National Influenza Surveillance Data and Search Queries from Mobile Devices and Desktops in South Korea. PLOS ONE 2016;11(7):e0158539CrossRef
- Tozzi AE, Gesualdo F, D’Ambrosio A, Pandolfi E, Agricola E, Lopalco P. Can Digital Tools Be Used for Improving Immunization Programs?. Frontiers in Public Health 2016;4CrossRef
- Santillana M, Nguyen AT, Dredze M, Paul MJ, Nsoesie EO, Brownstein JS, Salathé M. Combining Search, Social Media, and Traditional Data Sources to Improve Influenza Surveillance. PLOS Computational Biology 2015;11(10):e1004513CrossRef
- 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):e138CrossRef
- Katsuki T, Mackey TK, Cuomo R. Establishing a Link Between Prescription Drug Abuse and Illicit Online Pharmacies: Analysis of Twitter Data. Journal of Medical Internet Research 2015;17(12):e280CrossRef
- Mollema L, Harmsen IA, Broekhuizen E, Clijnk R, De Melker H, Paulussen T, Kok G, Ruiter R, Das E. Disease Detection or Public Opinion Reflection? Content Analysis of Tweets, Other Social Media, and Online Newspapers During the Measles Outbreak in the Netherlands in 2013. Journal of Medical Internet Research 2015;17(5):e128CrossRef
- Domnich A, Panatto D, Signori A, Lai PL, Gasparini R, Amicizia D, Olson DR. Age-Related Differences in the Accuracy of Web Query-Based Predictions of Influenza-Like Illness. PLOS ONE 2015;10(5):e0127754CrossRef
According to Crossref, the following books are citing this article (DOI 10.2196/jmir.3416)
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