Abstract
The enormous volumes of data generated by web users are the basis of several research activities in a new innovative field of research: online forecasting. Online forecasting is associated with the proper computation of web users’ data with the aim to arrive at accurate predictions of the future in several areas of human socio-economic activity. In this paper an algorithm is applied in order to predict the results of the Greek referendum held in 2015, using as input the data generated by users of the Google search engine. The proposed algorithm allows us to predict the results of the referendum with great accuracy. We strongly believe that due to the high internet penetration, as well as, the high usage of web search engines, the proper analysis of data generated by web search users reveals useful information about people preferences and/or future actions in several areas of human activity.
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Notes
- 1.
In order to assist other researchers to verify our results, the graphs contained the figures are the ones provided by the Google Trends service.
- 2.
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Polykalas, S.E., Prezerakos, G.N. (2017). Predicting Human Behavior Based on Web Search Activity: Greek Referendum of 2015. In: Angelov, P., Manolopoulos, Y., Iliadis, L., Roy, A., Vellasco, M. (eds) Advances in Big Data. INNS 2016. Advances in Intelligent Systems and Computing, vol 529. Springer, Cham. https://doi.org/10.1007/978-3-319-47898-2_1
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DOI: https://doi.org/10.1007/978-3-319-47898-2_1
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