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dc.contributor.authorGauthier, Robert
dc.contributor.authorPelletier, Catherine
dc.contributor.authorCarrier, Laurie-Ann
dc.contributor.authordionne, Maude
dc.contributor.authorDubé, Ève
dc.contributor.authorMeyer, Samantha B.
dc.contributor.authorWallace, James
dc.date.accessioned2023-02-07 15:03:03 (GMT)
dc.date.available2023-02-07 15:03:03 (GMT)
dc.date.issued2023-01
dc.identifier.urihttps://doi.org/10.1145/3567552
dc.identifier.urihttp://hdl.handle.net/10012/19156
dc.description© Gauthier, Pelletier, Carrier, Dionne, Dube, Meyer, Wallace | ACM, 2023. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in Proceedings of the ACM on Human-Computer Interaction, https://doi.org/10.1145/3567552.en
dc.description.abstractComputational techniques offer a means to overcome the amplified complexity and resource-intensity of qualitative research on online communities. However, we lack an understanding of how these techniques are integrated by researchers in practice, and how to address concerns about researcher agency in the qualitative research process. To explore this gap, we deployed the Computational Thematic Analysis Toolkit to a team of public health researchers, and compared their analysis to a team working with traditional tools and methods. Each team independently conducted a thematic analysis of a corpus of comments from Canadian news sites to understand discourses around vaccine hesitancy. We then compared the analyses to investigate how computational techniques may have influenced their research process and outcomes. We found that the toolkit provided access to advanced computational techniques for researchers without programming expertise, facilitated their interaction and interpretation of the data, but also found that it influenced how they approached their thematic analysis.en
dc.description.sponsorshipNSERC, Discovery Grant 2015-06585 || Canadian Immunization Research Network, Grant FRN\#151944en
dc.language.isoenen
dc.publisherACMen
dc.relation.ispartofseriesProceedings of the ACM on Human-Computer Interaction;
dc.subjectcase studyen
dc.subjectfield deploymenten
dc.subjectcomparisonen
dc.subjectthematic analysisen
dc.subjectcomputational methodsen
dc.titleAgency and Amplification: A Comparison of Manual and Computational Thematic Analyses by Public Health Researchersen
dc.typeArticleen
dcterms.bibliographicCitationRobert P. Gauthier, Catherine Pelletier, Laurie-Ann Carrier, Maude Dionne, Ève Dubé, Samantha Meyer, and James R. Wallace. 2023. Agency and Amplification: A Comparison of Manual and Computational Thematic Analyses by Public Health Researchers. Proc. ACM Hum.-Comput. Interact. 7, GROUP, Article 2 (January 2023), 22 pages. https://doi.org/10.1145/3567552en
uws.contributor.affiliation1Faculty of Healthen
uws.contributor.affiliation2School of Public Health Sciencesen
uws.typeOfResourceTexten
uws.peerReviewStatusRevieweden
uws.scholarLevelFacultyen
uws.scholarLevelGraduateen


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