Leveraging Podcasts as Academic Resources: A Seven-step Methodological Guide
: Kulkov, Ignat; Kulkova, Julia; Rohrbeck, Rene; Menvielle, Loick
Publisher: SAGE PUBLICATIONS INC
: THOUSAND OAKS
: 2024
: International Journal of Qualitative Methods
: INTERNATIONAL JOURNAL OF QUALITATIVE METHODS
: INT J QUAL METH
: 23
: 1
: 13
: 13
: 1609-4069
: 1609-4069
DOI: https://doi.org/10.1177/16094069241266197
: https://doi.org/10.1177/16094069241266197
: https://research.utu.fi/converis/portal/detail/Publication/457577859
This article introduces a novel seven-step methodology designed to incorporate podcasts as qualitative data sources in academic research, addressing a notable gap in current literature. The purpose of this methodology is to harness the unique and timely insights offered by podcasts, thereby enriching academic studies with diverse, real-time perspectives. The design of this approach includes a meticulous selection of podcasts based on relevance and credibility, comprehensive ethical considerations, strategic sampling methods, robust data collection and analysis techniques, and recommendations for applying best research practices. Key to this methodology is the use of weighted scoring systems to mitigate biases and the establishment of ethical guidelines specifically tailored for podcast data. The results of this study indicate the high potential of the proposed methodology in employing podcasts as an additional source of data, providing dynamic and current perspectives often absent in traditional research sources. Future studies are encouraged to delve deeper into refining and standardizing the proposed methodology, focusing on enhancing the weight metrics through advanced statistical techniques and exploring new technological tools for more efficient podcast data extraction and analysis.Graphical Abstract
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The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was partially sponsored by the Jenny and Antti Wihuri Foundation, Finland. This research was partially sponsored by the research center XPRES (Excellence in Production Research) – a strategic research area in Sweden.
