Predicting referendum results in the Big Data Era

Amaryllis Mavragani,Konstantinos P Tsagarakis

doi:10.1186/s40537-018-0166-z

Amaryllis Mavragani, Konstantinos P Tsagarakis

Open Access

https://doi.org/10.1186/s40537-018-0166-z

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Abstract

In addressing the challenge of Big Data Analytics, what has been of notable significance is the analysis of online search traffic data in order to analyze and predict human behavior. Over the last decade, since the establishment of the most popular such tool, Google Trends, the use of online data has been proven valuable in various research fields, including -but not limited to- medicine, economics, politics, the environment, and behavior. In the field of politics, given the inability of poll agencies to always well approximate voting intentions and results over the past years, what is imperative is to find new methods of predicting elections and referendum outcomes. This paper aims at presenting a methodology of predicting referendum results using Google Trends; a method applied and verified in six separate occasions: the 2014 Scottish Referendum, the 2015 Greek Referendum, the 2016 UK Referendum, the 2016 Hungarian Referendum, the 2016 Italian Referendum, and the 2017 Turkish Referendum. Said referendums were of importance for the respective country and the EU as well, and received wide international attention. Google Trends has been empirically verified to be a tool that can accurately measure behavioral changes as it takes into account the users’ revealed and not the stated preferences. Thus we argue that, in the time of intelligence excess, Google Trends can well address the analysis of social changes that the internet brings.

Highlights

Big Data are large data volumes characterized by the 8 Vs: ‘Volume’ [1], Variety, Velocity [2], Variability, Value, Volatility, Validity, and Veracity [3]
As Internet penetration is significantly growing in western countries and the significance of the Internet cannot be doubted [29], the monitoring and analysis of online search traffic data can be proven valuable in nowcasting election and referendum races
This section consists of the results of six referendums in the European Continent over the last years (2014–2017), namely the 2014 Scottish Independence Referendum, the 2015 Greek Bailout Referendum, the 2016 UK European Union Membership Referendum, the 2016 Hungarian Migrant Quota Referendum, the 2016 Italian Constitutional Referendum, and the 2017 Turkish Constitutional Referendum

Summary

Introduction

Big Data are large data volumes characterized by the 8 Vs: ‘Volume’ [1], Variety, Velocity [2], Variability, Value, Volatility, Validity, and Veracity [3]. Burnap et al [30] suggest that changes in online behavior can be accurately depicted on Internet data, while political campaigners increasingly use social media and online platforms [31]. Up to this point, the field of predicting referendum results using online search traffic data has not been much explored, though Google Trends’ data have been employed to predict the results of the 2015 Greek Referendum [14]

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