在 15 分钟城市概念背景下利用大数据分析华沙的美食服务

BUILDER Pub Date : 2024-07-15 DOI:10.5604/01.3001.0054.6685
Piotr Kamiński
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引用次数: 0

摘要

本文采用基于大数据的专有算法,结合用户评论和当前价格水平等定性数据,对华沙的美食服务基础设施进行了分析。它以城市尺度像素图的形式将服务网络的质量、差距和功能障碍可视化,为城市规划提供了新的见解。作者假定网络化社会是社会结构的基线,共享经济和平台资本主义是新的经济模式,并提出了一个分析框架,将城市划分为长度为 1200 米的像素点,代表 15 分钟的步行距离。所提出的分析结构以像素/节点矩阵的形式回应了平台城市主义的出现。在这些假设条件下,利用谷歌地图 API 的大数据,使用 Python 编写的专有算法对华沙的美食服务进行了分析。节点的研究参数包括变化、从用户评价推断出的质量以及价格水平(可获得性),参考了拉赫曼对数字权力的分析。这项研究是在 2024 年 1 月针对关键词 "餐厅 "进行的。该工具可以获取城市服务基础设施现状的数据并将其可视化,通过将结果叠加到传统地图上得出结论。作为作者博士论文的一部分,还进行了进一步的研究。该工具具有可移植性和可扩展性,可以根据给定的关键词对任何城市进行研究,同时获取定量和定性数据,这是该研究的一个显著特点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of Warsaw's Gastronomic Services Using Big Data in the Context of the 15-Minute City Concept
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.
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