International comparison of active citizenship by using Twitter data, the case of England and the Netherlands

Authors

  • Cristina Rosales Sánchez DG Joint Research Centre, Eurpean Commission, Ispra (Italy) Laboratory of Geo-information Science and Remote Sensing, Wageningen University and Research Centre, Wageningen (The Netherlands) http://orcid.org/0000-0001-8355-9747

DOI:

https://doi.org/10.5210/fm.v23i6.8273

Keywords:

Twitter, active citizenship, social media, survey, indicators, data mining

Abstract

Can social media become the new data source for certain social indicators? What does social media offer in comparison with classical sources for official statistics? This research analyzes the potential of Twitter data to obtain indicators of active citizenship. We use a methodology developed for a case study in Spain and test its replicability by applying it to England and the Netherlands. Twitter data offers an advantage to assess change in active citizenship over time and at high spatial resolution, while survey data — traditional sources for official statistics — are more authoritative and robust. Collecting and analyzing Twitter data is also faster than traditional survey processes. However, we found that Twitter usage specificities in each country ease or hinder the process, affecting the time to secure an indicator. Whilst future research will focus on other social indicators and sources of data, this research is an important step in developing an evidence-based understanding of the strengths and weakness of social media to inform policies.

Author Biography

Cristina Rosales Sánchez, DG Joint Research Centre, Eurpean Commission, Ispra (Italy) Laboratory of Geo-information Science and Remote Sensing, Wageningen University and Research Centre, Wageningen (The Netherlands)

PhD candidate

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Published

2018-06-01

How to Cite

Rosales Sánchez, C. (2018). International comparison of active citizenship by using Twitter data, the case of England and the Netherlands. First Monday, 23(6). https://doi.org/10.5210/fm.v23i6.8273