Topic Modeling and Text Analysis for Qualitative Policy Research.
This paper contributes to a critical methodological discussion that has direct ramifications for policy studies: how computational methods can be concretely incorporated into existing processes of textual analysis and interpretation without compromising scientific integrity. We focus on the computat...
| Publicado en: | Policy Studies Journal Vol. 49; no. 1; pp. 300 - 325 |
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| Autores principales: | , , |
| Formato: | Artículo |
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Wiley-Blackwell
Feb2021
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=148865359&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 148865359 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 0190292X PSJ jtl: Policy Studies Journal issn: 0190292X maglogo: Y pubinfo: dt: Feb2021 vid: 49 iid: 1 pid: 480 pub: Wiley-Blackwell artinfo: ui: 148865359 10.1111/psj.12343 ppf: 300 ppct: 25 formats: fmt: – @attributes: type: T – @attributes: type: C – @attributes: type: P size: 1.3MB tig: atl: Topic Modeling and Text Analysis for Qualitative Policy Research. aug: au: Isoaho, Karoliina Gritsenko, Daria Mäkelä, Eetu su: Policy sciences Computer simulation Machine learning Mixed methods research Latent semantic analysis Algorithms sug: subj: Policy sciences Computer simulation Machine learning Mixed methods research Latent semantic analysis Algorithms keyword: big data machine learning mixed‐method research qualitative research topic model big data machine learning mixed‐method research qualitative research topic model ab: This paper contributes to a critical methodological discussion that has direct ramifications for policy studies: how computational methods can be concretely incorporated into existing processes of textual analysis and interpretation without compromising scientific integrity. We focus on the computational method of topic modeling and investigate how it interacts with two larger families of qualitative methods: content and classification methods characterized by interest in words as communication units and discourse and representation methods characterized by interest in the meaning of communicative acts. Based on analysis of recent academic publications that have used topic modeling for textual analysis, our findings show that different mixed‐method research designs are appropriate when combining topic modeling with the two groups of methods. Our main concluding argument is that topic modeling enables scholars to apply policy theories and concepts to much larger sets of data. That said, the use of computational methods requires genuine understanding of these techniques to obtain substantially meaningful results. We encourage policy scholars to reflect carefully on methodological issues, and offer a simple heuristic to help identify and address critical points when designing a study using topic modeling. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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