A first look at global news coverage of disasters by using the GDELT dataset

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages300-308
Number of pages9
Volume8851
ISBN (Print)9783319137339
Publication statusPublished - 2014
Event6th International Conference on Social Informatics, SocInfo 2014 - Barcelona
Duration: 11 Nov 201413 Nov 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8851
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other6th International Conference on Social Informatics, SocInfo 2014
CityBarcelona
Period11/11/1413/11/14

Fingerprint

Disaster
Disasters
Coverage
Mixed Effects
Geography
Regression Model
Determinant
Monitor
Damage
Series

Keywords

  • Disaster
  • Foreign news
  • GDELT
  • Global news coverage
  • International news agency
  • News geography
  • Regionalism
  • Theory of newsworthiness

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Kwak, H., & An, J. (2014). A first look at global news coverage of disasters by using the GDELT dataset. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8851, pp. 300-308). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8851). Springer Verlag.

A first look at global news coverage of disasters by using the GDELT dataset. / Kwak, Haewoon; An, Jisun.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8851 Springer Verlag, 2014. p. 300-308 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8851).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Kwak, H & An, J 2014, A first look at global news coverage of disasters by using the GDELT dataset. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 8851, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8851, Springer Verlag, pp. 300-308, 6th International Conference on Social Informatics, SocInfo 2014, Barcelona, 11/11/14.
Kwak H, An J. A first look at global news coverage of disasters by using the GDELT dataset. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8851. Springer Verlag. 2014. p. 300-308. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Kwak, Haewoon ; An, Jisun. / A first look at global news coverage of disasters by using the GDELT dataset. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8851 Springer Verlag, 2014. pp. 300-308 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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