Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

11-2014

Abstract

In this work, we reveal the structure of global news coverage of disasters and its determinants by using a large-scale news coverage dataset collected by the GDELT (Global Data on Events, Location, and Tone) project that monitors news media in over 100 languages from the whole world. Significant variables in our hierarchical (mixed-effect) regression model, such as population, political stability, damage, and more, are well aligned with a series of previous research. However, we find strong regionalism in news geography, highlighting the necessity of comprehensive datasets for the study of global news coverage.

Keywords

GDELT, global news coverage, news geography, regionalism, theory of newsworthiness, international news agency, foreign news, disaster

Discipline

Numerical Analysis and Scientific Computing

Research Areas

Data Science and Engineering

Publication

Proceedings of 6th International Conference on Social Informatics, SocInfo 2014, Barcelona, Spain, November 11-13

Volume

8851

First Page

300

Last Page

308

ISBN

9783319137339

Identifier

10.1007/978-3-319-13734-6_22

Publisher

Springer Verlag

City or Country

Switzerland

Additional URL

https://link.springer.com/chapter/10.1007/978-3-319-13734-6_22

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