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Type of Publication: | Journal article |
Publication status: | Published |
URI (citable link): | http://nbn-resolving.de/urn:nbn:de:bsz:352-0-375657 |
Author: | Donnay, Karsten; Filimonov, Vladimir |
Year of publication: | 2014 |
Published in: | EPJ Data Science ; 3 (2014). - 25. - eISSN 2193-1127 |
DOI (citable link): | https://dx.doi.org/10.1140/epjds/s13688-014-0025-x |
Summary: |
The quantitative study of violent conflict and its mechanisms has in recent years greatly benefited from the availability of detailed event data. With a number of highly visible studies both in the natural sciences and in political science using such data to shed light on the complex mechanisms underlying violent conflict, researchers have recently raised issues of systematic (reporting) biases. While many sources of bias are qualitatively known, biases in event data are usually not studied with quantitative methods. In this study we focus on a unique case - the conflict in Iraq - that is covered by two independently collected datasets: Iraq Body Count (IBC) reports of civilian casualties and Significant Action (SIGACT) military data. We systematically identify a number of key quantitative differences between the event reporting in the two datasets and demonstrate that even for subsets where both datasets are most consistent at an aggregate level, the daily time series and timing signatures of events differ significantly. This suggests that at any level of analysis the choice of dataset may substantially affect any inferences drawn, with attendant consequences for a number of recent studies of the conflict in Iraq. We further outline how the insights gained from our analysis of conflict event data have broader implications for studies using similar data on other social processes.
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Subject (DDC): | 320 Politics |
Keywords: | event data, reporting bias, conflict, Iraq |
Link to License: | Attribution 2.0 Generic |
DONNAY, Karsten, Vladimir FILIMONOV, 2014. Views to a war : systematic differences in media and military reporting of the war in Iraq. In: EPJ Data Science. 3, 25. eISSN 2193-1127. Available under: doi: 10.1140/epjds/s13688-014-0025-x
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