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
Citation
1
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://link.springer.com/chapter/10.1007/978-3-319-13734-6_22