The proliferation of social media has resulted in its extensive use as a valuable source of information for researchers. This paper aims to use Twitter data to analyze and visualize tweets about the migration crisis in the European Union from 2016 to 2021. The paper uses a methodology to structure data for better understanding of complex social media data. The methods and metrics include the facet model of location based social media, the HyperLogLog data structure and novel uses of the metric typicality. The authors have also developed a web based interactive application closely following the methodology used to organize the dataset. Additionally the work also includes maps using spatial typicality which could be utilized for studying spatial phenomenon. The case study selected also provides unique insights and sets a template for working with multi-lingual geo-social media data. The authors believe that these methods and metrics could be reproduced for other case studies and aid in understanding and communication geo-social media data.
|Number of pages||16|
|Journal||KN - Journal of Cartography and Geographic Information|
|Publication status||Published - Sept 2022|
ASJC Scopus subject areas
- User generated data, EU migration crisis, Social media, Twitter, Geospatial visualization, User generated data, EU migration crisis, Social media, Twitter, Geospatial visualization