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WordCommentsAnalyzer: A windows software tool for qualitative research
Department of Psychology, University of Tehran, Tehran, Iran.
Department of Psychology, University of Tehran, Tehran, Iran.
Department of Psychology, University of Tehran, Tehran, Iran.
Örebro universitet, Institutionen för juridik, psykologi och socialt arbete. Center for Health and Medical Psychology, Örebro University, Örebro, Sweden.ORCID-id: 0000-0002-9862-3032
2018 (engelsk)Inngår i: F1000 Research, E-ISSN 2046-1402, Vol. 7, artikkel-id 536Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

There is a lack of free software that provides a professional and smooth experience in text editing and markup for qualitative data analysis. Word processing software like Microsoft Word provides a good editing experience, allowing the researcher to effortlessly add comments to text portions. However, organizing the keywords and categories in the comments can become a more difficult task when the amount of data increases. We present WordCommentsAnalyzer, a software tool that is written in C# using .NET Framework and OpenXml, which helps a qualitative researcher to organize codes when using Microsoft Word as the primary text markup software. WordCommentsAnalyzer provides an effective user interface to count codes, to organize codes in a code hierarchy, and to see various data extracts belonging to each code. It also offers basic visualization tools. We illustrate how to use this software by conducting a preliminary content analysis on Tweets with the #successfulaging hashtag. We also demonstrate that the software has satisfactory performance on a large dataset of Iranian journals abstracts. We hope this open-source software will facilitate qualitative data analysis by researchers who are interested in using Word for this purpose.

sted, utgiver, år, opplag, sider
F1000 Research Ltd , 2018. Vol. 7, artikkel-id 536
Emneord [en]
Code hierarchy tree, Coding, Comments, Computer assisted qualitative data analysis software, Microsoft Word, Thematic analysis
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Identifikatorer
URN: urn:nbn:se:oru:diva-87241DOI: 10.12688/f1000research.14819.2PubMedID: 30271579Scopus ID: 2-s2.0-85054368548OAI: oai:DiVA.org:oru-87241DiVA, id: diva2:1499148
Tilgjengelig fra: 2020-11-06 Laget: 2020-11-06 Sist oppdatert: 2020-11-09bibliografisk kontrollert

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