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Identifying Networks in Social Media: The case of #Grexit

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Listed:
  • Georgios Magkonis

    (University of Portsmouth)

  • Karen Jackson

    (University of Westminster)

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 data. 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 study presents a useful tool for identifying clusters. This is part of a new research agenda utilising the information extracted from big data available via social media channels.

Suggested Citation

  • Georgios Magkonis & Karen Jackson, 2019. "Identifying Networks in Social Media: The case of #Grexit," Networks and Spatial Economics, Springer, vol. 19(1), pages 319-330, March.
    • Handle: RePEc:kap:netspa:v:19:y:2019:i:1:d:10.1007_s11067-018-9399-9
    DOI: 10.1007/s11067-018-9399-9
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