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

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

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 var...

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Bibliographic Details
Main Authors: KWAK, Haewoon, AN, Jisun.
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2014
Subjects:
GDELT
global news coverage
news geography
regionalism
theory of newsworthiness
international news agency
foreign news
disaster
Numerical Analysis and Scientific Computing
Online Access:https://ink.library.smu.edu.sg/sis_research/6066
https://ink.library.smu.edu.sg/context/sis_research/article/7069/viewcontent/Kwak_An2014_Chapter_AFirstLookAtGlobalNewsCoverage.pdf
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Institution: Singapore Management University
Language: English
Description
Summary: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.

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