The limits of studying networks via event data: Evidence from the ICEWS dataset

Jäger, Kai

Additional URL:
Document Type: Article
Year of publication: 2018
The title of a journal, publication series: Journal of Global Security Studies
Volume: 3
Issue number: 4
Page range: 498-511
Place of publication: Oxford
Publishing house: Oxford University Press
ISSN: 2057-3170 , 2057-3189
Publication language: English
Institution: Außerfakultäre Einrichtungen > Mannheim Centre for European Social Research - Research Department B
Subject: 320 Political science
Abstract: Machine-coded event datasets have become popular in conflict research. I argue that systematic media biases render news-based event data unsuitable for studying networks of insurgents and political parties. Insurgent networks are too secretive to be captured by media reports, whereas alliances among regular political parties are too constant to be considered newsworthy. I analyze the data accuracy of the network study of insurgents and political parties in Thailand by Metternich et al. (2013), which is based on the most comprehensive event dataset currently available: Lockheed Martin's International Crisis Early Warning System (ICEWS) project. Using simple evaluation criteria, I show that most of the network data entries are incorrect, leading to a depiction of the networks that is unrelated to real-world cleavages in Thailand. While my hand-coded event dataset captures relatively more network-relevant information than ICEWS, the comparison confirms that journalists specifically underreport cooperative events among insurgents and parties. In addition, the ICEWS project provides unreliable counts of conflictual events in Thailand. Using alternative conflict measurements from the Deep South Watch dataset and a dummy variable based on established periods of unrest, I show that violent activities in Thailand's Deep South declined during periods of conflict between pro- and anti-Thaksin groups. Conflicts were unrelated to network fragmentation, contradicting the primary finding of Metternich et al.

Dieser Eintrag ist Teil der Universitätsbibliographie.

Metadata export


+ Search Authors in

BASE: Jäger, Kai

Google Scholar: Jäger, Kai

+ Page Views

Hits per month over past year

Detailed information

You have found an error? Please let us know about your desired correction here: E-Mail

Actions (login required)

Show item Show item