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On the Popularity of Internet of Things Projects in Online Communities

Author

Listed:
  • Taher Ahmed Ghaleb

    (Queen’s University)

  • Daniel Alencar da Costa

    (University of Otago)

  • Ying Zou

    (Queen’s University)

Abstract

Online Internet of Things (IoT) communities allow IoT engineers to publish information about their projects to a wider audience of users. Despite the growing adoption of IoT technologies in business, the popularity of IoT projects remains unexplored. Understanding how to improve the popularity of IoT projects helps project owners attract more users and foster business opportunities. In this paper, we explore the important characteristics of popular IoT projects across three facets: views count, respects count, and trending scores. We study over 18,000 IoT projects hosted on Hackster.io—a large online IoT community. In particular, we perform a time-series clustering to identify the evolution of each of the three popularity facets. In addition, we construct linear mixed-effect models to investigate the most important factors associated with the popularity of IoT projects. We provide insights to online IoT communities to improve the user guidelines to help (new) IoT engineers make their projects more eye-catching.

Suggested Citation

  • Taher Ahmed Ghaleb & Daniel Alencar da Costa & Ying Zou, 2022. "On the Popularity of Internet of Things Projects in Online Communities," Information Systems Frontiers, Springer, vol. 24(5), pages 1601-1634, October.
    • Handle: RePEc:spr:infosf:v:24:y:2022:i:5:d:10.1007_s10796-021-10157-1
    DOI: 10.1007/s10796-021-10157-1
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    References listed on IDEAS

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    1. Mike Thelwall & Kevan Buckley & Georgios Paltoglou & Di Cai & Arvid Kappas, 2010. "Sentiment strength detection in short informal text," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(12), pages 2544-2558, December.
    2. Ravi Sen, 2006. "Open Source Software Development Projects: Determinants of Project Popularity," EERI Research Paper Series EERI_RP_2006_02, Economics and Econometrics Research Institute (EERI), Brussels.
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    4. Mike Thelwall & Kevan Buckley & Georgios Paltoglou & Di Cai & Arvid Kappas, 2010. "Sentiment strength detection in short informal text," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(12), pages 2544-2558, December.
    5. Hua (Jonathan) Ye & Cecil Eng Huang Chua & Jun Sun, 2019. "Enhancing mobile data services performance via online reviews," Information Systems Frontiers, Springer, vol. 21(2), pages 441-452, April.
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