Identifying networks in social media: the case of #Grexit

Georgios Magkonis, Karen Jackson

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Abstract

We examine the intensity of ‘#Grexit’ usage in Twitter during a period of economic and financial turbulence. Using a frequency-analysis technique, we illustrate that we can extract detailed information from social media. This allows us to map the networks of interest as it is reflected in Twitter. Our findings identify high-interest in Grexit from Twitter users in key peripheral countries, core Eurozone members as well as core EU member states outside the Eurozone. Overall, our analysis provides a useful tool for identifying clusters. This is one first step towards the development of a new research agenda that aims to take advantage of the information that can be extracted from big data readily available via social media channels.
Original languageEnglish
Number of pages12
JournalNetworks and Spatial Economics
Early online date29 Mar 2018
DOIs
Publication statusEarly online - 29 Mar 2018

Keywords

  • networks
  • big data
  • Twitter
  • geo-location data
  • Grexit

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