Identifying networks in social media: The case of #Grexit

Jackson, K. and Magkonis, G. 2019. Identifying networks in social media: The case of #Grexit. Networks and Spatial Economics. 19 (1), p. 319–330. https://doi.org/10.1007/s11067-018-9399-9

TitleIdentifying networks in social media: The case of #Grexit
TypeJournal article
AuthorsJackson, K. and Magkonis, G.
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.

KeywordsNetworks
Big data
Twitter
Geo-location data
Grexit
JournalNetworks and Spatial Economics
Journal citation19 (1), p. 319–330
ISSN1566-113X
Year2019
PublisherSpringer
Accepted author manuscript
Digital Object Identifier (DOI)https://doi.org/10.1007/s11067-018-9399-9
Publication dates
Published online29 Mar 2018
Published29 Mar 2018
Published in printMar 2019

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