Does Web News Media have Opinions? Evidence from Real Estate Market Prediction

In this paper, we propose a novel method for real estate price prediction using web new media sentiments by incorporating human searching behaivor on the web. By combining online daily news’ sentiments and Google search engine query data, we construct a web news content and online search behavior-based integrated model for real estate prediction. Besides these factors, real estate price time series data are also considered into the model in order to improve the forecasting performance. Furthermore, we make a comparison between the integrated model and the baseline model without search engine query data. Experimental results indicate that the integrated model outperforms the non-integrated model, which suggests that online user searching behavior is of great value in enhancing the prediction performance. These findings imply that the proposed integrated model is effective and feasible for real estate market prediction.

[1]  Daphne Koller,et al.  Support Vector Machine Active Learning with Applications to Text Classification , 2002, J. Mach. Learn. Res..

[2]  Chih-Chou Chiu,et al.  Financial time series forecasting using independent component analysis and support vector regression , 2009, Decis. Support Syst..

[3]  G. C. Tiao,et al.  Journal of the American Statistical Association Forecasting the U.s. Unemployment Rate Forecasting the U.s. Unemployment Rate , 2022 .

[4]  E. Brynjolfsson,et al.  The Future of Prediction: How Google Searches Foreshadow Housing Prices and Sales , 2013, ICIS 2013.

[5]  Simla Tokgoz,et al.  A Quantitative Analysis of Trade Policy Responses to High Agricultural Commodity Prices , 2009 .

[6]  Isabelle Guyon,et al.  An Introduction to Variable and Feature Selection , 2003, J. Mach. Learn. Res..

[7]  Bernhard Schölkopf,et al.  New Support Vector Algorithms , 2000, Neural Computation.

[8]  Vladimir Vapnik,et al.  An overview of statistical learning theory , 1999, IEEE Trans. Neural Networks.

[9]  D. Sornette,et al.  Is there a real-estate bubble in the US? , 2005, physics/0506027.

[10]  P. Cashin,et al.  Booms and Slumps in World Commodity Prices , 1999, SSRN Electronic Journal.

[11]  Tun‐Hsiang Edward Yu,et al.  A quantitative analysis of trade policy responses to higher world agricultural commodity prices , 2011 .

[12]  Cory J. Butz,et al.  Rough support vector regression , 2010, Eur. J. Oper. Res..

[13]  D. Basak,et al.  Support Vector Regression , 2008 .

[14]  Wei Xu,et al.  Financial Market Prediction Based On Online Opinion Ensemble , 2012, PACIS.

[15]  Michael L. Mussa.  Global Economic Prospects , 2002 .

[16]  Max Kummerow,et al.  Information and communication technology in the real estate industry: productivity, industry structure and market efficiency , 2005 .

[17]  Hsinchun Chen,et al.  A quantitative stock prediction system based on financial news , 2009, Inf. Process. Manag..

[18]  Jeremy Ginsberg,et al.  Detecting influenza epidemics using search engine query data , 2009, Nature.

[19]  A. Bardhan,et al.  Global Financial Integration and Real Estate Security Returns , 2007 .

[20]  Bernhard Schölkopf,et al.  A tutorial on support vector regression , 2004, Stat. Comput..

[21]  Cheng Cheng,et al.  Data mining for unemployment rate prediction using search engine query data , 2012, Service Oriented Computing and Applications.

[22]  Erik Brynjolfsson,et al.  The Future of Prediction: How Google Searches Foreshadow Housing Prices and Quantities , 2009, ICIS.

[23]  Prem Melville,et al.  Sentiment analysis of blogs by combining lexical knowledge with text classification , 2009, KDD.

[24]  Johan Bollen,et al.  Twitter Mood as a Stock Market Predictor , 2011, Computer.

[25]  Hao Xie,et al.  Research on the sustainability of China's real estate market , 2011 .

[26]  Jianguo Sun,et al.  Rough nu-support vector regression , 2009, Expert Syst. Appl..

[27]  Mike Y. Chen,et al.  Yahoo! for Amazon: Sentiment Extraction from Small Talk on the Web , 2007, Manag. Sci..

[28]  Chih-Jen Lin,et al.  LIBSVM: A library for support vector machines , 2011, TIST.

[29]  Chih-Hung Wu,et al.  A Novel hybrid genetic algorithm for kernel function and parameter optimization in support vector regression , 2009, Expert Syst. Appl..

[30]  Pengyang Xie.  Development Ranking in Real Estate Strategy Management in China Based on TOPSIS Method , 2008, 2008 ISECS International Colloquium on Computing, Communication, Control, and Management.