Integrating Conflict Event Data

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DONNAY, Karsten, Eric T. DUNFORD, Erin C. MCGRATH, David BACKER, David E. CUNNINGHAM, 2019. Integrating Conflict Event Data. In: Journal of Conflict Resolution. 63(5), pp. 1337-1364. ISSN 0022-0027. eISSN 1552-8766. Available under: doi: 10.1177/0022002718777050

@article{Donnay2019Integ-45178, title={Integrating Conflict Event Data}, year={2019}, doi={10.1177/0022002718777050}, number={5}, volume={63}, issn={0022-0027}, journal={Journal of Conflict Resolution}, pages={1337--1364}, author={Donnay, Karsten and Dunford, Eric T. and McGrath, Erin C. and Backer, David and Cunningham, David E.} }

<rdf:RDF xmlns:dcterms="" xmlns:dc="" xmlns:rdf="" xmlns:bibo="" xmlns:dspace="" xmlns:foaf="" xmlns:void="" xmlns:xsd="" > <rdf:Description rdf:about=""> <dcterms:rights rdf:resource=""/> <dspace:isPartOfCollection rdf:resource=""/> <dcterms:isPartOf rdf:resource=""/> <foaf:homepage rdf:resource="http://localhost:8080/jspui"/> <dc:language>eng</dc:language> <dc:creator>Backer, David</dc:creator> <dcterms:title>Integrating Conflict Event Data</dcterms:title> <dc:creator>Dunford, Eric T.</dc:creator> <dc:creator>Cunningham, David E.</dc:creator> <dspace:isPartOfCollection rdf:resource=""/> <dcterms:isPartOf rdf:resource=""/> <dc:contributor>McGrath, Erin C.</dc:contributor> <dc:rights>terms-of-use</dc:rights> <dc:creator>McGrath, Erin C.</dc:creator> <dc:contributor>Cunningham, David E.</dc:contributor> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dc:contributor>Backer, David</dc:contributor> <dcterms:available rdf:datatype="">2019-02-23T12:41:07Z</dcterms:available> <dc:creator>Donnay, Karsten</dc:creator> <dcterms:issued>2019</dcterms:issued> <dcterms:hasPart rdf:resource=""/> <dspace:hasBitstream rdf:resource=""/> <dc:contributor>Dunford, Eric T.</dc:contributor> <dcterms:abstract xml:lang="eng">The growing multitude of sophisticated event-level data collection enables novel analyses of conflict. Even when multiple event data sets are available, researchers tend to rely on only one. We instead advocate integrating information from multiple event data sets. The advantages include facilitating analysis of relationships between different types of conflict, providing more comprehensive empirical measurement, and evaluating the relative coverage and quality of data sets. Existing integration efforts have been performed manually, with significant limitations. Therefore, we introduce Matching Event Data by Location, Time and Type (MELTT)—an automated, transparent, reproducible methodology for integrating event data sets. For the cases of Nigeria 2011, South Sudan 2015, and Libya 2014, we show that using MELTT to integrate data from four leading conflict event data sets (Uppsala Conflict Data Project–Georeferenced Event Data, Armed Conflict Location and Event Data, Social Conflict Analysis Database, and Global Terrorism Database) provides a more complete picture of conflict. We also apply multiple systems estimation to show that each of these data sets has substantial missingness in coverage.</dcterms:abstract> <bibo:uri rdf:resource=""/> <dc:contributor>Donnay, Karsten</dc:contributor> <dc:date rdf:datatype="">2019-02-23T12:41:07Z</dc:date> </rdf:Description> </rdf:RDF>

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