Published on 04.07.16 in Vol 18, No 7 (2016): July
Works citing "Estimating Influenza Outbreaks Using Both Search Engine Query Data and Social Media Data in South Korea"
According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.4955):
(note that this is only a small subset of citations)
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Chang Y, Chiang W, Wang W, Lin C, Hung L, Tsai Y, Chen Y. Assessing Epidemic Diseases and Public Opinion through Popular Search Behavior Using Non-English Language Google Trends (Preprint). JMIR Public Health and Surveillance 2018;
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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)
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Cheng H, Wu Y, Lin M, Liu Y, Tsai Y, Wu J, Pan K, Ke C, Chen C, Liu D, Lin I, Chuang J. Applying Machine Learning Models with An Ensemble Approach for Accurate Real-Time Influenza Forecasting in Taiwan: Development and Validation Study. Journal of Medical Internet Research 2020;22(8):e15394
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Joshi A, Karimi S, Sparks R, Paris C, Macintyre CR. Survey of Text-based Epidemic Intelligence. ACM Computing Surveys 2020;52(6):1
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Joshi A, Sparks R, McHugh J, Karimi S, Paris C, MacIntyre CR. Harnessing Tweets for Early Detection of an Acute Disease Event. Epidemiology 2020;31(1):90
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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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Zhang Z, Zheng X, Zeng DD, Leischow SJ. Tracking Dabbing Using Search Query Surveillance: A Case Study in the United States. Journal of Medical Internet Research 2016;18(9):e252
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Pesälä S, Virtanen MJ, Sane J, Jousimaa J, Lyytikäinen O, Murtopuro S, Mustonen P, Kaila M, Helve O. Health Care Professionals’ Evidence-Based Medicine Internet Searches Closely Mimic the Known Seasonal Variation of Lyme Borreliosis: A Register-Based Study. JMIR Public Health and Surveillance 2017;3(2):e19
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Nguyen QC, Li D, Meng H, Kath S, Nsoesie E, Li F, Wen M. Building a National Neighborhood Dataset From Geotagged Twitter Data for Indicators of Happiness, Diet, and Physical Activity. JMIR Public Health and Surveillance 2016;2(2):e158
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Menachemi N, Rahurkar S, Rahurkar M. Using Web-Based Search Data to Study the Public’s Reactions to Societal Events: The Case of the Sandy Hook Shooting. JMIR Public Health and Surveillance 2017;3(1):e12
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Samaras L, García-Barriocanal E, Sicilia M. Syndromic Surveillance Models Using Web Data: The Case of Influenza in Greece and Italy Using Google Trends. JMIR Public Health and Surveillance 2017;3(4):e90
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Carpenter JS, Groves D, Chen CX, Otte JL, Miller WR. Menopause and big data: Word Adjacency Graph modeling of menopause-related ChaCha data. Menopause 2017;24(7):783
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Cousins HC, Cousins CC, Harris A, Pasquale LR. Regional Infoveillance of COVID-19 Case Rates: Analysis of Search-Engine Query Patterns. Journal of Medical Internet Research 2020;22(7):e19483
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Liang F, Guan P, Wu W, Huang D. Forecasting influenza epidemics by integrating internet search queries and traditional surveillance data with the support vector machine regression model in Liaoning, from 2011 to 2015. PeerJ 2018;6:e5134
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Vuong Q, Ho M, Vuong T, La V, Ho M, Nghiem KP, Tran BX, Giang H, Giang T, Latkin C, Nguyen HT, Ho CS, Ho RC. Artificial Intelligence vs. Natural Stupidity: Evaluating AI readiness for the Vietnamese Medical Information System. Journal of Clinical Medicine 2019;8(2):168
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Chen Y, Zhang Y, Xu Z, Wang X, Lu J, Hu W. Avian Influenza A (H7N9) and related Internet search query data in China. Scientific Reports 2019;9(1)
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Raghupathi V, Zhou Y, Raghupathi W. Exploring Big Data Analytic Approaches to Cancer Blog Text Analysis. International Journal of Healthcare Information Systems and Informatics 2019;14(4):1
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Alessa A, Faezipour M. Flu Outbreak Prediction Using Twitter Posts Classification and Linear Regression With Historical Centers for Disease Control and Prevention Reports: Prediction Framework Study. JMIR Public Health and Surveillance 2019;5(2):e12383
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Choi SB, Ahn I, Zhang J. Forecasting seasonal influenza-like illness in South Korea after 2 and 30 weeks using Google Trends and influenza data from Argentina. PLOS ONE 2020;15(7):e0233855
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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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Ahmad AR, Murad HR. The Impact of Social Media on Panic During the COVID-19 Pandemic in Iraqi Kurdistan: Online Questionnaire Study. Journal of Medical Internet Research 2020;22(5):e19556
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Kaveh-Yazdy F, Zareh-Bidoki A. Search engines, news wires and digital epidemiology: Presumptions and facts. International Journal of Medical Informatics 2018;115:53
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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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Huang H, Peng Z, Wu H, Xie Q. A big data analysis on the five dimensions of emergency management information in the early stage of COVID-19 in China. Journal of Chinese Governance 2020;5(2):213
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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):e251
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. Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206
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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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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
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Venkatesh U, Gandhi PA. Prediction of COVID-19 Outbreaks Using Google Trends in India: A Retrospective Analysis. Healthcare Informatics Research 2020;26(3):175
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Chang Y, Chiang W, Wang W, Lin C, Hung L, Tsai Y, Suen J, Chen Y. Google Trends-based non-English language query data and epidemic diseases: a cross-sectional study of the popular search behaviour in Taiwan. BMJ Open 2020;10(7):e034156
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Nguyen QC, Brunisholz KD, Yu W, McCullough M, Hanson HA, Litchman ML, Li F, Wan Y, VanDerslice JA, Wen M, Smith KR. Twitter-derived neighborhood characteristics associated with obesity and diabetes. Scientific Reports 2017;7(1)
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Chen S, Liu X, Wu Y, Xu G, Zhang X, Mei S, Zhang Z, O'Meara M, O'Gara MC, Tan X, Li L. The application of meteorological data and search index data in improving the prediction of HFMD: A study of two cities in Guangdong Province, China. Science of The Total Environment 2019;652:1013
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Park S, Suh Y, Kim J, Kwon J. Analysis for internet health counseling about precocious puberty using text mining and topic modeling. Korean Journal of Health Education and Promotion 2020;37(3):71
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Zhu G, Li L, Zheng Y, Zhang X, Zou H. Forecasting Influenza Based on Autoregressive Moving Average and Holt-Winters Exponential Smoothing Models. Journal of Advanced Computational Intelligence and Intelligent Informatics 2021;25(1):138
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Corsi A, de Souza FF, Pagani RN, Kovaleski JL. Big data analytics as a tool for fighting pandemics: a systematic review of literature. Journal of Ambient Intelligence and Humanized Computing 2021;12(10):9163
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Radwan E, Radwan A, Radwan W. The role of social media in spreading panic among primary and secondary school students during the COVID-19 pandemic: An online questionnaire study from the Gaza Strip, Palestine. Heliyon 2020;6(12):e05807
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Ivanova I, Yaresko K, Prosianyk O, Zyma O, Starkova H. Information war and mission in profession of a journalist: the evolution of the world view of media students. Intercultural Communication 2022;7(1):17
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Hwang S, Kim S, Hwang S. Seasonal Variation for Plantar Fasciitis: Evidence from Google Trends Search Query Data. Healthcare 2022;10(9):1676
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Liu R, Huang YC, Sun J, Lau J, Cai Q. A Shot in the Arm for Vaccination Intention: The Media and the Health Belief Model in Three Chinese Societies. International Journal of Environmental Research and Public Health 2022;19(6):3705
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Rizqullah MF, Syakurah RA. Analysis of public search interest regarding government containment policy on COVID-19 new cases in Indonesia, Malaysia and Singapore. Health Promotion Perspectives 2021;11(3):360
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Ben S, Xin J, Chen S, Jiang Y, Yuan Q, Su L, Christiani DC, Zhang Z, Du M, Wang M. Global internet search trends related to gastrointestinal symptoms predict regional COVID-19 outbreaks. Journal of Infection 2022;84(1):56
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Tang H, Qiu Y, Guo Y, Liu J. Comparison of Periodic Behavior of Consumer Online Searches for Restaurants in the U.S. and China Based on Search Engine Data. IEEE Access 2018;6:34109
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Lee C, Wang D, Lyu S, Evans RD, Li L. A digital transformation-enabled framework and strategies for public health risk response and governance: China's experience. Industrial Management & Data Systems 2023;123(1):133
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De Toni G, Consonni C, Montresor A, Rocha LM. A general method for estimating the prevalence of influenza-like-symptoms with Wikipedia data. PLOS ONE 2021;16(8):e0256858
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Elbarazi I, Saddik B, Grivna M, Aziz F, Elsori D, Stip E, Bendak E. The Impact of the COVID-19 “Infodemic” on Well-Being: A Cross-Sectional Study. Journal of Multidisciplinary Healthcare 2022;Volume 15:289
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Li Q, Pan Q, Xie L. Prediction of Spread Trend of Epidemic Based on Spatial-Temporal Sequence. Symmetry 2022;14(5):1064
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Hwang SM, Lee GH, Oh SY. Correlation between Internet Search Query Data and the Health Insurance Review & Assessment Service Data for Seasonality of Plantar Fasciitis. Journal of Korean Foot and Ankle Society 2021;25(3):126
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Lee JY, Lee E. What topics are women interested in during pregnancy: exploring the role of social media as informational and emotional support. BMC Pregnancy and Childbirth 2022;22(1)
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Athanasiou M, Fragkozidis G, Zarkogianni K, Nikita KS. Long Short-term Memory–Based Prediction of the Spread of Influenza-Like Illness Leveraging Surveillance, Weather, and Twitter Data: Model Development and Validation. Journal of Medical Internet Research 2023;25:e42519
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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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Yang J, Zhou J, Luo T, Xie Y, Wei Y, Mai H, Yang Y, Cui P, Ye L, Liang H, Huang J. Predicting pulmonary tuberculosis incidence in China using Baidu search index: an ARIMAX model approach. Environmental Health and Preventive Medicine 2023;28:68
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Yan Q, Shan S, Zhang B, Sun W, Sun M, Luo Y, Zhao F, Guo X. Monitoring the Relationship between Social Network Status and Influenza Based on Social Media Data. Disaster Medicine and Public Health Preparedness 2023;17
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Li Y, Zhou X, Lyu Z. Regional contagion in health behaviors: evidence from COVID-19 vaccination modeling in England with social network theorem. Journal of Computational Social Science 2024;
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According to Crossref, the following books are citing this article (DOI 10.2196/jmir.4955):
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Lazar J, Feng JH, Hochheiser H. Research Methods in Human Computer Interaction. 2017. :411
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Samaras L, García-Barriocanal E, Sicilia M. Innovation in Health Informatics. 2020. :39
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Nawaz MS, Mustafa RU, Lali MIU. Applying Big Data Analytics in Bioinformatics and Medicine. 2018. chapter 11:272
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Tabassum M, Perumal S, Mohanan S, Suresh P, Cheriyan S, Hassan W. Design Methodologies and Tools for 5G Network Development and Application. 2021. chapter 6:109
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Almahdi MH, Raees BS. Artificial Intelligence for Sustainable Finance and Sustainable Technology. 2022. Chapter 29:284
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Raghupathi V, Zhou Y, Raghupathi W. Research Anthology on Big Data Analytics, Architectures, and Applications. 2022. chapter 90:1843
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