使用点评数据探测城市商业服务设施的发展规律

doi:10.11947/j.AGCS.2015.20140556

测绘学报 ›› 2015, Vol. 44 ›› Issue (9): 1022-1028.doi: 10.11947/j.AGCS.2015.20140556

使用点评数据探测城市商业服务设施的发展规律

蒋波涛^1,2, 王艳东¹, 叶信岳³

1. 武汉大学测绘遥感信息工程国家重点实验室, 湖北武汉 430079;
2. 宁波市规划与地理信息中心, 浙江宁波 315041;
3. 肯特州立大学地理系, 俄亥俄肯特 44242

收稿日期:2014-10-29 修回日期:2015-05-10 出版日期:2015-09-24 发布日期:2015-09-24
作者简介:蒋波涛(1981—),男,博士生,高级工程师,主要从事时空数据挖掘及社会化时空大数据在城市中的应用研究。E-mail:chiangbt@icloud.com
基金资助:
国家自然科学基金(41271399);国家科技支撑计划(2012BAH35B03);高等学校博士学科点专项科研基金(20120141110036);测绘地理信息公益性行业科研专项经费(201512015)

Detecting Development Pattern of Urban Business Facilities Using Reviews Data

JIANG Botao^1,2, WANG Yandong¹, YE Xinyue³

1. State Key Laboratory of Information Engineering in Surveying, Mapping & Remote Sensing, Wuhan University, Wuhan 430079, China;
2. Ningbo Planning and Geographic Information Center, Ningbo 315041, China;
3. Department of Geography, Kent State University, Kent, Ohio 44242, USA

Received:2014-10-29 Revised:2015-05-10 Online:2015-09-24 Published:2015-09-24
Supported by:
The National Natural Science Foundation of China (No.41271399) The National Key Technology Research and Development Program of the Ministry of Science and Technology of China (No.2012BAH35B03) Specialized Research Fund for the Doctoral Program of Higher Education(No.20120141110036) China Special Fund for Surveying,Mapping and Geoinformation Research in the Public Interest (No.201512015)

摘要/Abstract

摘要： 大众点评网提供的商业设施及其满意度评价数据为城市商业设施的时空分布与发展规律研究提供了一个重要的信息源,它们来源于分布在道路两侧的商业设施。根据此特征,本文设计了一种基于道路网约束的反映商业服务设施与交通网络关系的密度计算方法,对点评数据中蕴含的设施空间分布、设施数量与其满意度之间关系进行了分析。它将商业设施在空间上的二维分布映射至一维的道路网上,更真实地反映了商业服务设施与所处交通环境的影响,揭示了商业服务设施位置、数量及其满意度之间的关系,为城市规划的定量化研究提供了数值依据。

关键词: 商业服务设施, 道路网约束分析, 城市规划定量评价, 社交网络服务

Abstract: This paper reveals and utilizes the growing power of online customer reviews in the space and time context. The location of commercial facilities and online customer reviews offered by Dianping.com provide an important data source for the study of spatial and temporal dynamics of urban commercial facilities. The constraints of road network are taken into account towards computing the density of urban commercial facilities and associated online customer reviews, as well as their spatial distribution, temporal trend, and the coupling relationship between facility number and stratification level. This paper maps the spatial distribution of commercial facilities onto the nearby road network, reflecting the influences of the locations, number and satisfaction levels of other commercial facilities across various street types. Because more and more customers tend to make a final shopping decision by sorting through search results by ratings and feedback, the research conducted in this paper can provide the proof for quantitative evaluation of urban planning on commercial facility development.

Key words: commercial facilities, urban street network analysis, quantitative evaluation of urban planning, social network service

中图分类号:

P208

蒋波涛, 王艳东, 叶信岳. 使用点评数据探测城市商业服务设施的发展规律[J]. 测绘学报, 2015, 44(9): 1022-1028.

JIANG Botao, WANG Yandong, YE Xinyue. Detecting Development Pattern of Urban Business Facilities Using Reviews Data[J]. Acta Geodaetica et Cartographica Sinica, 2015, 44(9): 1022-1028.

参考文献

[1] PAUL L K, LINDA M. Urbanization[M]. GU Chaolin, TANG Peiyuan, YANG Xingzhu, et al. Trans. Beijing: Science Press, 2009: 1-3. (保罗·诺克斯, 琳达·迈克卡西. 城市化[M]. 顾朝林, 汤培源, 杨兴柱, 等译. 北京:科学出版社, 2009: 1-3.)
[2] YI Xiaoxiang. A Study on Community Retail and Service Facilities Based on Consumption Theories—The Case of Shanghai[J]. Urban Planning Forum, 2012, 10(3): 44-52. (衣霄翔. 消费视角下的居住区商业服务设施配建体系研究——以上海市曲阳新村为例[J]. 城市规划学刊, 2012, 10(3): 44-52.)
[3] TANG Zilai. The Formation Demand of the Service Facilities in Real Estate: The Trend Forecast and Practice Test[J]. City Planning Review, 1999, 23(5): 32-36. (唐子来. 居住小区服务设施的需求型态: 趋势推断和实证检验[J]. 城市规划, 1999, 23(5): 32-36.)
[4] XU Xiaoyan. Micro Location Layout of Neighborhood Facilities[J]. Planners, 2011, 27(12): 62-66. (徐晓燕. 城市社区配套设施微区位布局研究[J]. 规划师, 2011, 27(12): 62-66.)
[5] YAN Ruogu, ZHOU Suhong, YAN Xiaopei. Studies of Urban Regeneration[J]. Progress in Geography, 2011, 30(8): 947-955. (严若谷, 周素红, 闫小培. 城市更新之研究[J]. 地理科学进展, 2011, 30(8): 947-955.)
[6] DAI Fei, ZHANG Junhua. The Survey Methods in Planning and Design 1—Questionnaire Survey(Theory Part)[J]. Chinese Landscape Architecture, 2008, 24(10): 82-87. (戴菲, 章俊华. 规划设计学中的调查方法(1)——问卷调查法(理论篇)[J]. 中国园林, 2008, 24(10): 82-87.)
[7] SAKAKI T, OKAZAKI M, MATSUO Y. Earthquake Shakes Twitter Users: Real-Time Event Detection by Social Sensors[C]//Proceedings of the 19th International Conference on World Wide Web. Raleigh: ACM,2010: 851-860.
[8] GOODCHILD M F. Citizens as Sensors: the World of Volunteered Geography[J]. GeoJournal, 2007, 69(4): 211-221.
[9] HEIPKE C. Crowdsouring Geospatial Data[J]. ISPR Journal of Photogrammetry and Remote Sensing, 2010, 65(6): 550-557.
[10] HU Qingwu, WANG Ming, LI Qingquan. Urban Hotspot and Commercial Area Exploration with Check-in Data[J]. Acta Geodaetica et Cartographica Sinica, 2014, 43(3): 314-321. (胡庆武, 王明, 李清泉. 利用位置签到数据探索城市热点与商圈[J]. 测绘学报, 2014, 43(3): 314-321.)
[11] DAVIS JR C A, PAPPA G L, DE OLIVEIRA D R R, et al. Inferring the Location of Twitter Messages Based on User Relationships[J]. Transactions in GIS, 2011, 15(6): 735-751.
[12] LAMPOS V,CRISTIANINI N.Tracking the Flu Pandemic by Monitoring the Social Web[C]//2010 2nd International Workshop on Cognitive Information Processing (CIP). Elba: IEEE,2010: 411-416.
[13] HWANG M H, WINSLOW A. User Manual for GeoDaNet:Spatial Analysis on Undirected Networks[EB/OL]. [2012-03-22]. https://geodacenter.asu.edu/drupal_files/Geodanet_Manual_03_2012.pdf.
[14] LV Xiuying. The Current Situation of the Development of the Third Party Review Websites in China under the Web2.0—Dianping and Douban[J]. Journal of Southeast University:Philosophy and Social Science, 2011, 13(S1): 87-92. (吕秀莹. 浅析Web2.0环境下我国第三方点评网站的发展现状——以大众点评网和豆瓣网为例[J]. 东南大学学报: 哲学社会科学版, 2011, 13(S1): 87-92.)
[15] BLEI D M, NG A Y, JORDAN M I. Latent Dirichlet Allocation[J]. The Journal of Machine Learning Research, 2003, 3: 993-1022.
[16] BLEI D M, LAFFERTY J D. Dynamic Topic Models[C]//Proceedings of the 23rd International Conference on Machine Learning. New York:ACM,2006:113-120.
[17] DEERWESTER S, DUMAIS S T, Furnas G W, et al. Indexing by Latent Semantic Analysis[J]. Journal of the American Society for Information Science and Technology, 1990, 41(6): 391-407.
[18] TAO Chao, TAN Yihua, PENG Bifa, et al. A Probabilistic Latent Semantic Analysis Based Classification for High Resolution Remotely Sensed Imagery[J]. Acta Geodaetica et Cartographica Sinica, 2011, 40(2): 156-162. (陶超, 谭毅华, 彭碧发, 等. 一种基于概率潜在语义模型的高分辨率遥感影像分类方法[J]. 测绘学报, 2011, 40(2): 156-162.)
[19] XIE Zhixiao, YAN Jun. Kernel Density Estimation of Traffic Accidents in a Network Space[J]. Computers, Environment and Urban Systems, 2008, 32(5): 396-406.
[20] SHE Bing, ZHU Xinyan, GUO Wei, et al. Research on Spatial Pattern of City Events under Road Network Constraints[J]. Application Research of Computers, 2013, 30(8): 2327-2329. (佘冰, 朱欣焰, 呙维, 等. 道路网约束下的城市事件空间点模式分析[J]. 计算机应用研究, 2013, 30(8): 2327-2329.)
[21] OKABE A, SATOH T, SUGIHARA K. A Kernel Density Estimation Method for Networks, Its Computational Method and a GIS-based Tool[J]. International Journal of Geographical Information Science, 2009, 23(1): 7-32.

使用点评数据探测城市商业服务设施的发展规律

Detecting Development Pattern of Urban Business Facilities Using Reviews Data

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