当前位置:首页 > 报告详情

利用房地产门户网站上的广告来衡量建筑活动ESSnet WIN 工作包 3用例 2.pdf

上传人: Fl****zo 编号:718621 2025-06-22 17页 5.12MB

1、Measuring construction activities using advertisements from real estate portals.ESSnet WIN Work Package 3,Use Case 2WIN conference,Gdansk,February 4th-5th2025 Tobias Gramlich(Hesse State Statistical Office,Germany)Overall goalFrom ads appearing at online real estate portals:can we produce somemeanin

2、gful early estimate of the number of newly constructedbuildings that have become available in a specific year of reference?Implicit limitation by the way of data collection:become available on the(online)market in a specific year.We?SE-SCB,DE-AfS,DE-HSLCan we?Yes,we can!In principle.Well,Maybe,we co

3、uldnt in every detail.What do we need?data Ads from all“/several relevant portals,relevant info from each ad Over a longer period of time(three years)Either collect it or get it by means of an agreement Both typically mean you need to spend some money staff to program and maintain scrapers R and Pyt

4、hon some infrastructure to develop,test and run scrapers,to store data In our case:no production level,so no production level“infrastructure (gain)experience(to)make decisionsThings to decide,experience to gain Which portals to choose?Relevance,accesability,availabbility,reliability,stability,covera

5、ge,overlap Collect or buy?How to define or identify newly constructed objects“?Speficiation error,completeness,validity When to start scraping?How often to scrape?Prospective“scraping,scraping frequency(weekly,daily?Even shorter interval?)Undercoverage How to identify duplicates within and between d

6、ata sources?Completeness,validity,stabilityExamples:available characteristicsExample II:charcteristicsExamples:projects/deduplicationExample:prospective“scraping?Results for DE-HE:2023 Comparison of scraped ads vs.official statistics(completed buildings,2023)Overall coverage(ads to buildings):210%Ov

word格式文档无特别注明外均可编辑修改,预览文件经过压缩,下载原文更清晰!
三个皮匠报告文库所有资源均是客户上传分享,仅供网友学习交流,未经上传用户书面授权,请勿作商用。
本文研究了通过房地产门户网站的广告来衡量建筑活动的方法。研究目标是估算参考年内新建成并投放市场的建筑数量。主要发现如下: 1. 收集了长达三年的数据,使用R和Python编程语言开发、测试和运行数据抓取器。 2. 与官方统计数据相比,2022年抓取的广告数据显示,建筑物的整体覆盖率为130%,公寓为46%。 3. 覆盖率在不同地区有显著差异,城市地区较高,范围在10%至1000%之间。 4. 面临的挑战包括数据去重、数据缺失和偏差(城市地区广告覆盖率高)。 5. 2023年的数据显示,建筑物广告与官方统计的建筑数量相比,整体覆盖率为210%,公寓为70%。 文章强调了选择合适门户网站、定义新建筑对象、抓取频率和去重策略的重要性。尽管存在局限性,该方法仍为估计新建筑数量提供了一个有意义的早期指标。
"如何从房产广告估算新建房屋?" "在线房产广告能告诉我们什么?" 哪些因素关键?"
客服
商务合作
小程序
服务号
折叠