Qualitative Big Data’s Challenges and Solutions

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorSuvivuo, Sampsaen_US
dc.contributor.departmentDepartment of Information and Service Managementen_US
dc.date.accessioned2021-01-25T10:07:34Z
dc.date.available2021-01-25T10:07:34Z
dc.date.issued2021-01-05en_US
dc.description.abstractDigitalization of everyday lives has tremendously increased the amount of digital (trace) data of people’s behaviour available for researchers. However, traditional qualitative research methods struggle with the width and breadth of the data. This paper reviewed 61 recent studies that had utilized qualitative big data for the practical challenges they had encountered and how they were addressed. While quantitative and qualitative big data share many common issues, the review points at that lack of qualitative methods and dataset reduction required by algorithms in big data research decreases the richness of the qualitative data. Locating relevant data and reducing noise are further challenges. Currently, these challenges can be only partially addressed with a combination of human and computer pattern recognition and crowdsourcing. The review describes many “tricks of the trade” but abduction research and pragmatist philosophy seem promising starting places for a more pervasive framework.en
dc.description.versionPeer revieweden
dc.format.extent980-989
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationSuvivuo , S 2021 , Qualitative Big Data’s Challenges and Solutions : An Organizing Review . in Proceedings of the 54th Hawaii International Conference on System Sciences . Hawaii International Conference on System Sciences , pp. 980-989 , Annual Hawaii International Conference on System Sciences , Maui , Hawaii , United States , 05/01/2021 . < http://hdl.handle.net/10125/70731 >en
dc.identifier.isbn978-0-9981331-4-0
dc.identifier.otherPURE UUID: 04a993c2-6fc8-4ea0-a7f2-ae0962a7d33een_US
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/04a993c2-6fc8-4ea0-a7f2-ae0962a7d33een_US
dc.identifier.otherPURE LINK: http://hdl.handle.net/10125/70731en_US
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/55310190/Suvivuo_HICSS_paper.pdfen_US
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/102072
dc.identifier.urnURN:NBN:fi:aalto-202101251381
dc.language.isoenen
dc.relation.ispartofAnnual Hawaii International Conference on System Sciencesen
dc.relation.ispartofseriesProceedings of the 54th Hawaii International Conference on System Sciencesen
dc.rightsopenAccessen
dc.subject.keywordBig Data and Analytics: Pathways to Maturityen_US
dc.subject.keywordchallengesen_US
dc.subject.keyworddigital trace dataen_US
dc.subject.keywordqualitative big dataen_US
dc.subject.keywordreviewen_US
dc.titleQualitative Big Data’s Challenges and Solutionsen
dc.typeConference article in proceedingsfi
dc.type.versionpublishedVersion
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