Smart City Gnosys

Smart city article details

Title	Interpreting The Smart City Through Topic Modeling
ID_Doc	33169
Authors	Zheng Z.; Sieber R.E.
Year	2023
Published	Urban Book Series, Part F270
DOI	http://dx.doi.org/10.1007/978-3-031-31746-0_3
Abstract	The Canadian Smart Cities Challenge grant program provided a unique opportunity to investigate what communities across Canada mean when they propose becoming a smart city. We investigated the utility of human-centered machine learning to analyze 137 grant proposals submitted to this program, containing approximately 1.5 million words. We explored whether results generated by topic modeling aligned with or differed from standard smart city definitions in the literature and current urban applications of topic modeling. The analysis resulted in three main findings. First, the prevalence of topics describing rural, regional and Indigenous communities challenged conventional definitions of “city” in the smart city. Second, context (e.g., local culture and language) inferred what constitutes smart, although smartness was not focused on technical innovations. Finally, our abductive approach generated new insights missing from conventional smart city research methods, including 40 percent of finalists and all four winning cities being identified as most representative users of topics. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Author Keywords	Indigenous; Rural; Smart cities; Smart cities challenge; Topic modeling

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