Hindawi Complexity Volume 2019, Article ID 5370961, 15 pages https://doi.org/10.1155/2019/5370961 Research Article Evaluation of Residential Housing Prices on the Internet: Data Pitfalls Ming Li ,1 Guojun Zhang ,2 Yunliang Chen ,3 and Chunshan Zhou1 1 School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China 2School of Public Policy and Management, Guangdong University of Finance and Economics, Guangzhou 510275, China 3School of Computer Science, China University of Geosciences, Wuhan 430074, China Correspondence should be addressed to Guojun Zhang;
[email protected] and Yunliang Chen; Cyl
[email protected] Received 29 November 2018; Accepted 27 January 2019; Published 19 February 2019 GuestEditor:KeDeng Copyright © 2019 Ming Li et al. Tis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Many studies have used housing prices on the Internet real estate information platforms as data sources, but platforms difer in the nature and quality of the data they release. However, few studies have analysed these diferences or their efect on research. In this study, second-hand neighbourhood housing prices and information on fve online real estate information platforms in Guangzhou, China, were comparatively analysed and the performance of neighbourhoods’ raw information from four for-proft online real estate information platforms was evaluated by applying the same housing price model. Te comparison results show that the ofcial second-hand residential housing prices at city and district level are generally lower than those issued on four for- proft real estate websites.