System for Spatio-Temporal Analysis of Online News and Blogs
Previous work on spatio-temporal analysis of news items and other documents has largely focused on broad categorization of small text collections by region or country. A system for large-scale spatio-temporal analysis of online news media and blogs is presented, together with an analysis of global news media coverage over a nine year period. We demonstrate the benefits of using a hierarchical geospatial database to disambiguate between geographical named entities, and provide results for an extremely fine-grained analysis of news items. Aggregate maps of media attention for particular places around the world are compared with geographical and socio-economic data. Our analysis suggests that GDP per capita is the best indicator for media attention.
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