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A Comparison of Human Narrative Coding of Redemption and Automated Linguistic Analysis for Understanding Life Stories

Bibliographic Data

ID19280889
AuthorsSara J Weston (0000-0001-7782-6239, Washington University in St. Louis), Sanjiv Bhatia (corresponding author), Keith S Cox (0000-0003-3957-7205, Medical University of South Carolina), David M Condon (0000-0002-8406-783X, Northwestern University), J J Jackson (0000-0002-9490-8890, Washington University in St. Louis)
Year2016
Volume84
Issue5
Pages594-606
Publication date2016-10-01
Open AccessYes
TypeARTICLE
VenueJournal of Personality (JOURNAL)
Journal identifiersISSN: 0022-3506 • E-ISSN: 1467-6494
PublisherWiley (PUBLISHER • GB)
DOI10.1111/jopy.12183
PMID25982525
OpenAlexW25982525
LanguageEN
Citations received16
References cited43

The majority of life narrative research is performed using trained human coders. In contrast, automated linguistic analysis is oft employed in the study of verbal behaviors. These two methodological approaches are directly compared to determine the utility of automated linguistic analysis for the study of life narratives. In a study of in‐person interviews ( N = 158) and a second study of life stories collected online ( N = 242), redemption scores are compared to the output of the Linguistic Inquiry and Word Count (Pennebaker, Francis & Booth, 2001). Additionally, patterns of language are found using exploratory principal components analysis. In both studies, redemption scores are modestly correlated with some LIWC categories and unassociated with the components. Patterns of language do not replicate across samples, indicating that the structure of language does not extend to a broader population. Redemption scores and linguistic components are independent predictors of life satisfaction up to 3 years later. These studies converge on the finding that human‐coded redemption and automated linguistic analysis are complementary and nonredundant methods of analyzing life narratives, and considerations for the study of life narratives are discussed

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Citations per year1.78
Citation span2017 - 2026 (10)
Highly citedNo

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