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Autor/inNelson, Laura K.
TitelComputational Grounded Theory: A Methodological Framework
QuelleIn: Sociological Methods & Research, 49 (2020) 1, S.3-42 (40 Seiten)
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ZusatzinformationORCID (Nelson, Laura K.)
Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN0049-1241
DOI10.1177/0049124117729703
SchlagwörterGrounded Theory; Content Analysis; Expertise; Hermeneutics; Computer Use; Pattern Recognition; Artificial Intelligence; Natural Language Processing; Qualitative Research; Females; Social Change; Illinois (Chicago); New York (New York)
AbstractThis article proposes a three-step methodological framework called computational grounded theory, which combines expert human knowledge and hermeneutic skills with the processing power and pattern recognition of computers, producing a more methodologically rigorous but interpretive approach to content analysis. The first, pattern detection step, involves inductive computational exploration of text, using techniques such as unsupervised machine learning and word scores to help researchers to see novel patterns in their data. The second, pattern refinement step, returns to an interpretive engagement with the data through qualitative deep reading or further exploration of the data. The third, pattern confirmation step, assesses the inductively identified patterns using further computational and natural language processing techniques. The result is an efficient, rigorous, and fully reproducible computational grounded theory. This framework can be applied to any qualitative text as data, including transcribed speeches, interviews, open-ended survey data, or ethnographic field notes, and can address many potential research questions. (As Provided).
AnmerkungenSAGE 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
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2024/1/01
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