Google Flu Trendsand Mass Data: Extrapolated to Ebola?

Authors

  • Pilar Jose Lopez Lopez UCM

DOI:

https://doi.org/10.37467/gka-revtechno.v5.465

Keywords:

Data Journalism, Google Trends Flu, Spain, Ébola, Research

Abstract

Millions of people surf the Internet through the Google search engine. This company leveraging in-training your users  Google  Flu  Trends  developed  in  2008. This tool was  created  with  the  aim  of  collecting  data  for  the  incidence  of  influenza in a country with high precision. This application records queries that netizens through its search engine Google and the data obtained their own conclusions, as if from a study of epidemiology is involved. Three years later the development of this  tool, in 2011, the information  you  offer data did not resemble reality. What had happened? The Data Journalism was failing. Many users who did not have the flu seeking information on the Internet and Google Flu Trends counted them how sick. With this paper is to analyze this tool andcompare their progress and results with Ebola disease.

References

Casacuberta, D. (2013).Innovación, Big Data y Epidemiología.Revista Iberoamericana de Argumentación, 7.

Cook, S., Conrad, C., Fowlkes, A.L., (2011). Assessing Google flu trends perfor-mance in the Uni-ted States during the 2009 influenza virus A (H1N1) pandemic. Disponible en: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0023610

Fung, K. (2014). Google Flu Trends’ Failure Shows Good Data > Big Data. Harvard Business Review. Disponible el recurso online: https://hbr.org/2014/03/google-flu-trends-failure-shows-good-data-big-data/#signin

Ginsberg, J.; Mohebbi, M.H. (2009).Detecting influenza epidemics using search engine query data. Nature, 457(19). Disponible el recurso online: http://dx.doi.org/10.1038/nature07634

Jurado, E. (2015). Los errores de comunicación en la crisis del ébola.Cuadernos de Periodistas, 29.

Lazer, D., Kennedy, R., King, G. y Vespignani, A. (2014).The Parable of Google Flu: Traps in Big Data Analysis.Science, 343(6176), pp.1203–1205.

Pries, K.H.& Dunnigan, R. (2015). Big Data Analytics: A practical guide for managers. Boca Raton: CRC Press

Roncancio, G. E. (2009). Ayudas desde la red para el control de la epidemia. Infectio, 13(3), pp. 217-222. Retrieved March 23, 2015. Disponible el recurso online: http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S012393922009000300009&lng=en&tlng=es.

Tascón, M. (2013). Introducción: Big Data. Pasado, presente y futuro. Revista Telos, 95.

Valdivia Pérez, A., Benito M. A., Escortell Mayr, E. (2010) ¿Se puede predecir la epidemia de gripemediante datos de búsquedas en Internet? Gac Sanit.

Viktor, MS. & Kenneth, C. (2013). Big data: arevolutionthatwill transformhowwe live,work, andthink.British: Hodderand Stoughton.

Downloads

Published

2016-03-30

Issue

Section

Research articles

How to Cite

Google Flu Trendsand Mass Data: Extrapolated to Ebola?. (2016). TECHNO REVIEW. International Technology, Science and Society Review Revista Internacional De Tecnología, Ciencia Y Sociedad, 5(1), 157-163. https://doi.org/10.37467/gka-revtechno.v5.465