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
| Title | Identifying networks in social media: The case of #Grexit |
|---|---|
| Type | Journal article |
| Authors | Jackson, 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. |
| Keywords | Networks |
| Big data | |
| Geo-location data | |
| Grexit | |
| Journal | Networks and Spatial Economics |
| Journal citation | 19 (1), p. 319–330 |
| ISSN | 1566-113X |
| Year | 2019 |
| Publisher | Springer |
| Accepted author manuscript | |
| Digital Object Identifier (DOI) | https://doi.org/10.1007/s11067-018-9399-9 |
| Publication dates | |
| Published online | 29 Mar 2018 |
| Published | 29 Mar 2018 |
| Published in print | Mar 2019 |