Published on 14.11.14 in Vol 16, No 11 (2014): November
Works citing "The Reliability of Tweets as a Supplementary Method of Seasonal Influenza Surveillance"
According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.3532):
(note that this is only a small subset of citations)
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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):e161
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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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Stewart J, Sprivulis P, Dwivedi G. Artificial intelligence and machine learning in emergency medicine. Emergency Medicine Australasia 2018;30(6):870
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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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Zeraatkar K, Ahmadi M. Trends of infodemiology studies: a scoping review. Health Information & Libraries Journal 2018;35(2):91
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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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Djuricich AM, Zee-Cheng JE. Live tweeting in medicine: ‘Tweeting the meeting’. International Review of Psychiatry 2015;27(2):133
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Ukoha C, Stranieri A. Criteria to Measure Social Media Value in Health Care Settings: Narrative Literature Review. Journal of Medical Internet Research 2019;21(12):e14684
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Barnes M, Hanson C, Giraud-Carrier C. The Case for Computational Health Science. Journal of Healthcare Informatics Research 2018;2(1-2):99
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Sarker A, Magge A, Sharma A. Dermatologic concerns communicated through Twitter. International Journal of Dermatology 2017;56(8)
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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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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):e34
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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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. Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206
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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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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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Gao J, Zhang Y, Zhou T. Computational socioeconomics. Physics Reports 2019;817:1
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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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Chan MS, Lohmann S, Morales A, Zhai C, Ungar L, Holtgrave DR, Albarracín D. An Online Risk Index for the Cross-Sectional Prediction of New HIV Chlamydia, and Gonorrhea Diagnoses Across U.S. Counties and Across Years. AIDS and Behavior 2018;22(7):2322
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Shi X, Xue B, Tsou M, Ye X, Spitzberg B, Gawron JM, Corliss H, Lee J, Jin R. Detecting events from the social media through exemplar-enhanced supervised learning. International Journal of Digital Earth 2019;12(9):1083
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Zhao N, Cao G, Vanos JK, Vecellio DJ. The effects of synoptic weather on influenza infection incidences: a retrospective study utilizing digital disease surveillance. International Journal of Biometeorology 2018;62(1):69
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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
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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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Hassan Zadeh A, Zolbanin HM, Sharda R, Delen D. Social Media for Nowcasting Flu Activity: Spatio-Temporal Big Data Analysis. Information Systems Frontiers 2019;21(4):743
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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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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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Gardy JL, Loman NJ. Towards a genomics-informed, real-time, global pathogen surveillance system. Nature Reviews Genetics 2018;19(1):9
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. Research challenges and opportunities in mapping social media and Big Data. Cartography and Geographic Information Science 2015;42(sup1):70
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Braithwaite SR, Giraud-Carrier C, West J, Barnes MD, Hanson CL. Validating Machine Learning Algorithms for Twitter Data Against Established Measures of Suicidality. JMIR Mental Health 2016;3(2):e21
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Ye X, Li S, Yang X, Qin C. Use of Social Media for the Detection and Analysis of Infectious Diseases in China. ISPRS International Journal of Geo-Information 2016;5(9):156
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Park HW, Park S, Chong M. Conversations and Medical News Frames on Twitter: Infodemiological Study on COVID-19 in South Korea. Journal of Medical Internet Research 2020;22(5):e18897
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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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. 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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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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Hopkins RS, Tong CC, Burkom HS, Akkina JE, Berezowski J, Shigematsu M, Finley PD, Painter I, Gamache R, Vilas VJDR, Streichert LC. A Practitioner-Driven Research Agenda for Syndromic Surveillance. Public Health Reports 2017;132(1_suppl):116S
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Young SD, Zhang Q, Nishiura H. Using search engine big data for predicting new HIV diagnoses. PLOS ONE 2018;13(7):e0199527
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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
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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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Khan Y, Leung GJ, Belanger P, Gournis E, Buckeridge DL, Liu L, Li Y, Johnson IL. Comparing Twitter data to routine data sources in public health surveillance for the 2015 Pan/Parapan American Games: an ecological study. Canadian Journal of Public Health 2018;109(3):419
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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):205395171665291
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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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Little RJA, West BT, Boonstra PS, Hu J. Measures of the Degree of Departure from Ignorable Sample Selection. Journal of Survey Statistics and Methodology 2020;8(5):932
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Kim AE, Hopper T, Simpson S, Nonnemaker J, Lieberman AJ, Hansen H, Guillory J, Porter L. Using Twitter Data to Gain Insights into E-cigarette Marketing and Locations of Use: An Infoveillance Study. Journal of Medical Internet Research 2015;17(11):e251
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Wilson C, Jumbert MG. The new informatics of pandemic response: humanitarian technology, efficiency, and the subtle retreat of national agency. Journal of International Humanitarian Action 2018;3(1)
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Kumar S, Xu C, Ghildayal N, Chandra C, Yang M. Social media effectiveness as a humanitarian response to mitigate influenza epidemic and COVID-19 pandemic. Annals of Operations Research 2022;319(1):823
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Ramirez AG, Aguilar RP, Merck A, Despres C, Sukumaran P, Cantu-Pawlik S, Chalela P. Use of #SaludTues Tweetchats for the Dissemination of Culturally Relevant Information on Latino Health Equity: Exploratory Case Study. JMIR Public Health and Surveillance 2021;7(3):e21266
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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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Zhao Y, He X, Feng Z, Bost S, Prosperi M, Wu Y, Guo Y, Bian J. Biases in using social media data for public health surveillance: A scoping review. International Journal of Medical Informatics 2022;164:104804
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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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Bartmess M, Talbot C, O’Dwyer ST, Lopez RP, Rose KM, Anderson JG. Using Twitter to understand perspectives and experiences of dementia and caregiving at the beginning of the COVID-19 pandemic. Dementia 2022;21(5):1734
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Pilipiec P, Samsten I, Bota A, Rocha LM. Surveillance of communicable diseases using social media: A systematic review. PLOS ONE 2023;18(2):e0282101
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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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. Sport psychology practitioner's perceptions and use of social media. Asian Journal of Sport and Exercise Psychology 2022;2(3):156
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Kim I, Begay C, Ma HJ, Orozco FR, Rogers CJ, Valente TW, Unger JB. E-Cigarette–Related Health Beliefs Expressed on Twitter Within the U.S.. AJPM Focus 2023;2(2):100067
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Rosato C, Moore RE, Carter M, Heap J, Harris J, Storopoli J, Maskell S. Extracting Self-Reported COVID-19 Symptom Tweets and Twitter Movement Mobility Origin/Destination Matrices to Inform Disease Models. Information 2023;14(3):170
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Osborne MT, Kenah E, Lancaster K, Tien J. Catch the tweet to fight the flu: Using Twitter to promote flu shots on a college campus. Journal of American College Health 2023;71(8):2470
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Xie T, Ge Y, Xu Q, Chen S. Public Awareness and Sentiment Analysis of COVID-Related Discussions Using BERT-Based Infoveillance. AI 2023;4(1):333
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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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Wang A, Dara R, Yousefinaghani S, Maier E, Sharif S. A Review of Social Media Data Utilization for the Prediction of Disease Outbreaks and Understanding Public Perception. Big Data and Cognitive Computing 2023;7(2):72
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Sano Y, Hori A, Kolahi J. 12-year observation of tweets about rubella in Japan: A retrospective infodemiology study. PLOS ONE 2023;18(5):e0285101
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Boligarla S, Laison EKE, Li J, Mahadevan R, Ng A, Lin Y, Thioub MY, Huang B, Ibrahim MH, Nasri B. Leveraging machine learning approaches for predicting potential Lyme disease cases and incidence rates in the United States using Twitter. BMC Medical Informatics and Decision Making 2023;23(1)
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Deiner MS, Deiner NA, Hristidis V, McLeod SD, Doan T, Lietman TM, Porco TC. Use of Large Language Models to Assess the Likelihood of Epidemics From the Content of Tweets: Infodemiology Study. Journal of Medical Internet Research 2024;26:e49139
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According to Crossref, the following books are citing this article (DOI 10.2196/jmir.3532):
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Samaras L, García-Barriocanal E, Sicilia M. Innovation in Health Informatics. 2020. :39
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Ye X, Li S, Yang X, Lee J, Wu L. Big Data Support of Urban Planning and Management. 2018. Chapter 7:113
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Nayduch D, Fryxell RT, Olafson PU. Medical and Veterinary Entomology. 2019. :673
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. Routledge Handbook of Health Geography. 2018. :331
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Fan S, Garg S, Yeom S. AI 2016: Advances in Artificial Intelligence. 2016. Chapter 63:702
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Spitzberg BH, Tsou M, Jung C. The Handbook of Applied Communication Research. 2020. :163
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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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