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Analysis of Warsaw's Gastronomic Services Using Big Data in the Context of the 15-Minute City Concept

Autor(en): ORCID
Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Builder, , n. 8, v. 325
Seite(n): 14-18
DOI: 10.5604/01.3001.0054.6685
Abstrakt:

This paper analyzes the gastronomic service infrastructure of Warsaw using a proprietary algorithm based on big data, incorporating qualitative data such as user reviews and current price levels. It visualizes the quality of the service network, gaps, and dysfunctions in the form of pixel maps at city scale, providing new insights for urban planning. Assuming a networked society as the baseline social structure and the shared economy and platform capitalism as new economic models, the author proposes an analytical framework that divides the city into pixels with a length of 1200 meters, representing a 15-minute walking distance. The proposed analytical structure, in the form of a pixel/node matrix, responds to the emergence of platform urbanism. Under these assumptions, the gastronomic services of Warsaw were analyzed using a proprietary algorithm written in Python, utilizing big data from the Google Maps API. The research parameters for the nodes include variation, quality extrapolated from user ratings, and the price level (accessibility), referring to Rahman's analyses of digital power. The study was conducted for the keyword 'restaurant' in January 2024. The tool allows for the acquisition and visualization of data on the current state of the city service infrastructure and draws conclusions by overlaying the results on a conventional map. Further studies have also been conducted as part of the authors PhD. The tool is transferable and scalable, allowing research on any city based on given keywords, drawing both quantitative and qualitative data, which is a distinctive feature of the study.

Structurae kann Ihnen derzeit diese Veröffentlichung nicht im Volltext zur Verfügung stellen. Der Volltext ist beim Verlag erhältlich über die DOI: 10.5604/01.3001.0054.6685.
  • Über diese
    Datenseite
  • Reference-ID
    10798064
  • Veröffentlicht am:
    01.09.2024
  • Geändert am:
    01.09.2024
 
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