Computationally Intensive Research: Advancing a Role for Secondary Analysis of Qualitative Data

Kaveh Mohajeri and Amir Karami
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Kaveh Mohajeri: LEM - Lille économie management - UMR 9221 - UA - Université d'Artois - UCL - Université catholique de Lille - Université de Lille - CNRS - Centre National de la Recherche Scientifique
Amir Karami: UAB - University of Alabama at Birmingham [ Birmingham]

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Abstract: This paper draws attention to the potential of computational methods in reworking data generated in past qualitative studies. While qualitative inquiries often produce rich data through rigorous and resource-intensive processes, much of this data often remains unused. In this paper, we first make a general case for secondary analysis of qualitative data by discussing its benefits, distinctions, and epistemological aspects. We then argue for opportunities with computationally intensive secondary analysis, highlighting the possibility of drawing on data assemblages spanning multiple contexts and time frames to address cross-contextual and longitudinal research phenomena and questions. We propose a scheme to perform computationally intensive secondary analysis and advance ideas on how this approach can help facilitate the development of innovative research designs. Finally, we enumerate some key challenges and ongoing concerns associated with qualitative data sharing and reuse.

Date: 2025
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Published in Journal of the Association for Information Systems, 2025, 26 (3), pp.832-849. ⟨10.17705/1jais.00923⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05123084

DOI: 10.17705/1jais.00923

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