| Title | Data-driven Spatial Features Analysis Using Share of Voice in Commercial Area |
|---|---|
| ID_Doc | 41311 |
| Authors | Wang, SM; Yang, W |
| Title | Data-driven Spatial Features Analysis Using Share of Voice in Commercial Area |
| Year | 2021 |
| Published | |
| Abstract | Smart city strategies are now incorporating new data analytic resources and techniques to respond to the demands created in the urban networks' processes. This research offers new insight into a data-driven approach to knowing the city phenomena based on open data. With the contribution of emerging big data technologies, we explore the real-time virtual settings of the Share of Voice (SOV) data collected from the Google reviews and check-in statistics during "popular times" from online searches and collected business establishment tallies during opening hours. The purpose of this research is to shed light on a more comprehensive method for the employment of technical tools along with established theories involving urban configuration. This research contributes to the interdisciplinary study of urban spatial features from data-driven intelligent city planning and development. |
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