Qualitative Big Data’s Challenges and Solutions: An Organizing Review

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Abstract

Digitalization 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.
Original languageEnglish
Title of host publicationProceedings of the 54th Hawaii International Conference on System Sciences
PublisherHawaii International Conference on System Sciences
Pages980-989
ISBN (Electronic)978-0-9981331-4-0
Publication statusPublished - 5 Jan 2021
MoE publication typeA4 Conference publication
EventAnnual Hawaii International Conference on System Sciences - Virtual, Online, Maui, United States
Duration: 5 Jan 20218 Jan 2021
Conference number: 54

Conference

ConferenceAnnual Hawaii International Conference on System Sciences
Abbreviated titleHICSS
Country/TerritoryUnited States
CityMaui
Period05/01/202108/01/2021

Keywords

  • Big Data and Analytics: Pathways to Maturity
  • challenges
  • digital trace data
  • qualitative big data
  • review

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