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When Google got flu wrong

Citations

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Cited by:

  1. 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.
  2. 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.
  3. 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.
  4. Shu-Heng Chen & Ragupathy Venkatachalam, 2017. "Information aggregation and computational intelligence," Evolutionary and Institutional Economics Review, Springer, vol. 14(1), pages 231-252, June.
  5. 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.
  6. 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.
  7. 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.).
  8. 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.
  9. 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.
  10. 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.
  11. 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.
  12. 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).
  13. Pablo Pedraza & Ian Vollbracht, 2023. "General theory of data, artificial intelligence and governance," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-16, December.
  14. 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.
  15. 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.
  16. 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].
  17. 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.
  18. 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.
  19. 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.
  20. 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.
  21. 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).
  22. 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.
  23. 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.
  24. 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.
  25. Daniel Bjorkegren & Darrell Grissen, 2017. "Behavior Revealed in Mobile Phone Usage Predicts Loan Repayment," Papers 1712.05840, arXiv.org, revised Dec 2019.
  26. 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.
  27. 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.
  28. 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.
  29. 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.
  30. 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.
  31. Nicolas Woloszko, 2020. "Tracking activity in real time with Google Trends," OECD Economics Department Working Papers 1634, OECD Publishing.
  32. Cebrián, Eduardo & Domenech, Josep, 2024. "Addressing Google Trends inconsistencies," Technological Forecasting and Social Change, Elsevier, vol. 202(C).
  33. 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.
  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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