What Should We Do about Source Selection in Event Data? Challenges, Progress, and Possible Solutions
AffiliationUniv Arizona, Dept Sociol
MetadataShow full item record
PublisherROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
CitationWhat Should We Do about Source Selection in Event Data? Challenges, Progress, and Possible Solutions 2016, 46 (1):42 International Journal of Sociology
RightsCopyright © Taylor & Francis Group, LLC.
Collection InformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at firstname.lastname@example.org.
AbstractThe prospect of using the Internet and other Big Data methods to construct event data promises to transform the field but is stymied by the lack of a coherent strategy for addressing the problem of selection. Past studies have shown that event data have significant selection problems. In terms of conventional standards of representativeness, all event data have some unknown level of selection no matter how many sources are included. We summarize recent studies of news selection and outline a strategy for reducing the risks of possible selection bias, including techniques for generating multisource event inventories, estimating larger populations, and controlling for nonrandomness. These build on a relativistic strategy for addressing event selection and the recognition that no event data set can ever be declared completely free of selection bias.
NotePublished online: 08 Mar 2016; 18 Month Embargo.
VersionFinal accepted manuscript