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When Google got flu wrong

Citations

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Cited by:

  1. Schaer, Oliver & Kourentzes, Nikolaos & Fildes, Robert, 2019. "Demand forecasting with user-generated online information," International Journal of Forecasting, Elsevier, vol. 35(1), pages 197-212.
  2. Jiachen Sun & Peter A. Gloor, 2021. "Assessing the Predictive Power of Online Social Media to Analyze COVID-19 Outbreaks in the 50 U.S. States," Future Internet, MDPI, vol. 13(7), pages 1-13, July.
  3. Rivera, Roberto, 2016. "A dynamic linear model to forecast hotel registrations in Puerto Rico using Google Trends data," Tourism Management, Elsevier, vol. 57(C), pages 12-20.
  4. F. Antolini & L. Grassini, 2019. "Foreign arrivals nowcasting in Italy with Google Trends data," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(5), pages 2385-2401, September.
  5. Jun, Seung-Pyo & Yoo, Hyoung Sun & Lee, Jae-Seong, 2021. "The impact of the pandemic declaration on public awareness and behavior: Focusing on COVID-19 google searches," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
  6. Chris Allen & Ming-Hsiang Tsou & Anoshe Aslam & Anna Nagel & Jean-Mark Gawron, 2016. "Applying GIS and Machine Learning Methods to Twitter Data for Multiscale Surveillance of Influenza," PLOS ONE, Public Library of Science, vol. 11(7), pages 1-10, July.
  7. Siqing Shan & Qi Yan & Yigang Wei, 2020. "Infectious or Recovered? Optimizing the Infectious Disease Detection Process for Epidemic Control and Prevention Based on Social Media," IJERPH, MDPI, vol. 17(18), pages 1-25, September.
  8. Jose Ramon Albert & Arturo Martinez Jr. & Katrina Miradora & Jan Arvin Lapuz & Marymell Martillan & Criselda De Dios & Iva Sebastian-Samaniego, 2019. "Readiness of National Statistical Systems in Asia and the Pacific for Leveraging Big Data to Monitor the SDGs," Working Papers id:13017, eSocialSciences.
  9. Beate Franke & Jean-FRANçois Plante & Ribana Roscher & En-shiun Annie Lee & Cathal Smyth & Armin Hatefi & Fuqi Chen & Einat Gil & Alexander Schwing & Alessandro Selvitella & Michael M. Hoffman & Roger, 2016. "Statistical Inference, Learning and Models in Big Data," International Statistical Review, International Statistical Institute, vol. 84(3), pages 371-389, December.
  10. Cebrián, Eduardo & Domenech, Josep, 2024. "Addressing Google Trends inconsistencies," Technological Forecasting and Social Change, Elsevier, vol. 202(C).
  11. Katsikopoulos, Konstantinos V. & Şimşek, Özgür & Buckmann, Marcus & Gigerenzer, Gerd, 2022. "Transparent modeling of influenza incidence: Big data or a single data point from psychological theory?," International Journal of Forecasting, Elsevier, vol. 38(2), pages 613-619.
  12. Khatri, Vijay, 2016. "Managerial work in the realm of the digital universe: The role of the data triad," Business Horizons, Elsevier, vol. 59(6), pages 673-688.
  13. Mark Huberty, 2015. "Awaiting the Second Big Data Revolution: From Digital Noise to Value Creation," Journal of Industry, Competition and Trade, Springer, vol. 15(1), pages 35-47, March.
  14. Baki Cakici & Pedro Sanches, 2014. "Detecting the Visible: The Discursive Construction of Health Threats in a Syndromic Surveillance System Design," Societies, MDPI, vol. 4(3), pages 1-15, July.
  15. Shu-Heng Chen & Ragupathy Venkatachalam, 2017. "Information aggregation and computational intelligence," Evolutionary and Institutional Economics Review, Springer, vol. 14(1), pages 231-252, June.
  16. Krzysztof Bartosz Klimiuk & Dawid Krefta & Karol Kołkowski & Karol Flisikowski & Małgorzata Sokołowska-Wojdyło & Łukasz Balwicki, 2022. "Seasonal Patterns and Trends in Dermatoses in Poland," IJERPH, MDPI, vol. 19(15), pages 1-14, July.
  17. Steven Heston & Nitish R. Sinha, 2016. "News versus Sentiment : Predicting Stock Returns from News Stories," Finance and Economics Discussion Series 2016-048, Board of Governors of the Federal Reserve System (U.S.).
  18. Daniel E. O'Leary & Veda C. Storey, 2020. "A Google–Wikipedia–Twitter Model as a Leading Indicator of the Numbers of Coronavirus Deaths," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 27(3), pages 151-158, July.
  19. Zeynep Ertem & Dorrie Raymond & Lauren Ancel Meyers, 2018. "Optimal multi-source forecasting of seasonal influenza," PLOS Computational Biology, Public Library of Science, vol. 14(9), pages 1-16, September.
  20. Victor Olsavszky & Mihnea Dosius & Cristian Vladescu & Johannes Benecke, 2020. "Time Series Analysis and Forecasting with Automated Machine Learning on a National ICD-10 Database," IJERPH, MDPI, vol. 17(14), pages 1-17, July.
  21. Reto Cueni & Bruno S. Frey, 2014. "Forecasts and Reactivity," CREMA Working Paper Series 2014-10, Center for Research in Economics, Management and the Arts (CREMA).
  22. Pablo Pedraza & Ian Vollbracht, 2023. "General theory of data, artificial intelligence and governance," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-16, December.
  23. Jun, Seung-Pyo & Sung, Tae-Eung & Park, Hyun-Woo, 2017. "Forecasting by analogy using the web search traffic," Technological Forecasting and Social Change, Elsevier, vol. 115(C), pages 37-51.
  24. Ibrahim Musa & Hyun Woo Park & Lkhagvadorj Munkhdalai & Keun Ho Ryu, 2018. "Global Research on Syndromic Surveillance from 1993 to 2017: Bibliometric Analysis and Visualization," Sustainability, MDPI, vol. 10(10), pages 1-20, September.
  25. Dorner, Matthias & Haller, Peter, 2020. "Not coming in today - Firm productivity differentials and the epidemiology of the flu," IAB-Discussion Paper 202006, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
  26. Jun, Seung-Pyo & Park, Do-Hyung, 2016. "Consumer information search behavior and purchasing decisions: Empirical evidence from Korea," Technological Forecasting and Social Change, Elsevier, vol. 107(C), pages 97-111.
  27. Hongxin Xue & Yanping Bai & Hongping Hu & Haijian Liang, 2019. "Regional level influenza study based on Twitter and machine learning method," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-23, April.
  28. Emre Eftelioglu & Zhe Jiang & Reem Ali & Shashi Shekhar, 2016. "Spatial computing perspective on food energy and water nexus," Journal of Environmental Studies and Sciences, Springer;Association of Environmental Studies and Sciences, vol. 6(1), pages 62-76, March.
  29. Soo Beom Choi & Insung Ahn, 2020. "Forecasting seasonal influenza-like illness in South Korea after 2 and 30 weeks using Google Trends and influenza data from Argentina," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-14, July.
  30. Daniel Bjorkegren & Darrell Grissen, 2017. "Behavior Revealed in Mobile Phone Usage Predicts Loan Repayment," Papers 1712.05840, arXiv.org, revised Dec 2019.
  31. Krzysztof Drachal & Daniel González Cortés, 2022. "Estimation of Lockdowns’ Impact on Well-Being in Selected Countries: An Application of Novel Bayesian Methods and Google Search Queries Data," IJERPH, MDPI, vol. 20(1), pages 1-24, December.
  32. Wengao Lu & Jingxin Li & Jinsong Li & Danni Ai & Hong Song & Zhaojun Duan & Jian Yang, 2021. "Short-Term Impacts of Meteorology, Air Pollution, and Internet Search Data on Viral Diarrhea Infection among Children in Jilin Province, China," IJERPH, MDPI, vol. 18(21), pages 1-15, November.
  33. Nicolas Woloszko, 2020. "Tracking activity in real time with Google Trends," OECD Economics Department Working Papers 1634, OECD Publishing.
  34. Huberty, Mark, 2015. "Can we vote with our tweet? On the perennial difficulty of election forecasting with social media," International Journal of Forecasting, Elsevier, vol. 31(3), pages 992-1007.
  35. Jun, Seung-Pyo & Yoo, Hyoung Sun & Choi, San, 2018. "Ten years of research change using Google Trends: From the perspective of big data utilizations and applications," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 69-87.
  36. Arora, Vishal S. & McKee, Martin & Stuckler, David, 2019. "Google Trends: Opportunities and limitations in health and health policy research," Health Policy, Elsevier, vol. 123(3), pages 338-341.
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