提高我们对短期租活动的理解:对Airbnb列表的每日抓取方法
Yang Wang1, Mark Livingston1, David P McArthur1
1Urban Big Data Centre, University of Glasgow, Glasgow, Scotland, United Kingdom.
PloS one
|February 7, 2024
概括
详细的Airbnb日历数据显示了短期租活动,有助于城市住房政策. 这种方法为有效的干预策略提供了对市场动态的强有力的洞察力.
科学领域:
- 城市研究 城市研究
- 经济学 经济学 经济学
- 数据科学数据科学数据科学
背景情况:
- 在线短期租 (STR) 的扩张给城市住房供应带来了压力.
- 目前的数据限制阻碍了对STR市场的有效政策设计和评估.
研究的目的:
- 通过详细的清单数据开发和验证一种用于测量STR活动的新方法.
- 为政策分析提供STR列表活动水平的可靠指标.
主要方法:
- 系统地抓取每天的Airbnb列表日历.
- 对日历活动模式的解释,以定义列表活动指标.
- 在英国首次COVID-19封锁期间的分析,以展示该方法的价值.
主要成果:
- 一种新的方法,从公开可用的数据中推导出颗粒式的STR活动指标.
- 已定义的上市活动指标提供了对市场波动的详细见解.
- 这种方法在市场中断的独特时期 (英国COVID-19封锁) 证明有价值.
结论:
- 拟议的方法提供了一种严格而详细的方法来监测STR市场.
- 对STR活动的增强数据可以显著改善城市规划和住房政策.
- 这种方法为决策者和研究人员提供了一个可扩展的解决方案.
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