How Events Enter (or Not) Data Sets: The Pitfalls and Guidelines of Using Newspapers in the Study of Conflict

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Bibliographic Details
Title: How Events Enter (or Not) Data Sets: The Pitfalls and Guidelines of Using Newspapers in the Study of Conflict
Language: English
Authors: Demarest, Leila (ORCID 0000-0001-6887-9937), Langer, Arnim
Source: Sociological Methods & Research. May 2022 51(2):632-666.
Availability: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: http://sagepub.com
Peer Reviewed: Y
Page Count: 35
Publication Date: 2022
Document Type: Journal Articles
Reports - Descriptive
Descriptors: Guidelines, Research Methodology, Conflict, Social Science Research, Newspapers, Research Problems, Error of Measurement, Data Analysis
DOI: 10.1177/0049124119882453
ISSN: 0049-1241
Abstract: While conflict event data sets are increasingly used in contemporary conflict research, important concerns persist regarding the quality of the collected data. Such concerns are not necessarily new. Yet, because the methodological debate and evidence on potential errors remains scattered across different subdisciplines of social sciences, there is little consensus concerning proper reporting practices in codebooks, how best to deal with the different types of errors, and which types of errors should be prioritised. In this article, we introduce a new analytical framework--that is, the Total Event Error (TEE) framework--which aims to elucidate the methodological challenges and errors that may affect whether and how events are entered into conflict event data sets, drawing on different fields of study. Potential errors are diverse and may range from errors arising from the rationale of the media source (e.g., selection of certain types of events into the news) to errors occurring during the data collection process or the analysis phase. Based on the TEE framework, we propose a set of strategies to mitigate errors associated with the construction and use of conflict event data sets. We also identify a number of important avenues for future research concerning the methodology of creating conflict event data sets.
Abstractor: As Provided
Entry Date: 2022
Accession Number: EJ1337281
Database: ERIC
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Abstract:While conflict event data sets are increasingly used in contemporary conflict research, important concerns persist regarding the quality of the collected data. Such concerns are not necessarily new. Yet, because the methodological debate and evidence on potential errors remains scattered across different subdisciplines of social sciences, there is little consensus concerning proper reporting practices in codebooks, how best to deal with the different types of errors, and which types of errors should be prioritised. In this article, we introduce a new analytical framework--that is, the Total Event Error (TEE) framework--which aims to elucidate the methodological challenges and errors that may affect whether and how events are entered into conflict event data sets, drawing on different fields of study. Potential errors are diverse and may range from errors arising from the rationale of the media source (e.g., selection of certain types of events into the news) to errors occurring during the data collection process or the analysis phase. Based on the TEE framework, we propose a set of strategies to mitigate errors associated with the construction and use of conflict event data sets. We also identify a number of important avenues for future research concerning the methodology of creating conflict event data sets.
ISSN:0049-1241
DOI:10.1177/0049124119882453