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Understanding people’s attitudes in IoT systems using wellness probes and TF-IDF data analysis

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Abstract

This study explores the enhancement of Internet of Things (IoT) product design and development through the integration of ethnography and big data analytics. A new model is proposed, recognizing the limitations of existing big data approaches in capturing nuanced and complex user needs. This model combines in-depth analysis of user attitudes with extensive review data from current IoT product users, aiming to uncover a more comprehensive understanding of the user experience beyond typical quantitative insights provided by big data. An IoT product named 'Zipband' has been developed as a practical application of this integrated research methodology. A combination of qualitative and quantitative research methods, including interviews and term frequency–inverse document frequency (TF-IDF) scheme analysis, was utilized to identify diverse user needs and uncover new opportunities for user experience improvement. This research contributes to the field by introducing a data-driven ethnographic approach that has the potential to inspire convergence research in IoT product design and user experience areas.

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Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

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Funding

This research received no external funding.

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Author notes

  1. Sanghun Sul and Seung-Beom Cho contributed equally to this work.

Authors and Affiliations

  1. Department of Culture and Technology, Sungkyunkwan University, 25-2, Sungkyunkwan-ro, Jongno-gu, Seoul, 03063, Korea

    Sanghun Sul

  2. Department of Mechanical Engineering, Sungkyunkwan University, 25-2, Sungkyunkwan-ro, Jongno-gu, Seoul, 03063, Korea

    Seung-Beom Cho

Authors
  1. Sanghun Sul
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  2. Seung-Beom Cho
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Contributions

Conceptualization: [Sanghun Sul], …; Methodology: [Sanghun Sul], …; Formal analysis and investigation: [Sanghun Sul,Seung-Beom Cho], …; Writing - original draft preparation: [Sanghun Sul,Seung-Beom Cho]; Writing - review and editing: [Sanghun Sul,Seung-Beom Cho], …; Funding acquisition: [Sanghun Sul], …; Resources: [Sanghun Sul], …; Supervision: [Sanghun Sul].

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Correspondence to Sanghun Sul.

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Appendix

Appendix

Table 5 Participants' responses to each theme
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Sul, S., Cho, SB. Understanding people’s attitudes in IoT systems using wellness probes and TF-IDF data analysis. Multimed Tools Appl (2024). https://doi.org/10.1007/s11042-024-18830-8

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