A Real Estate Price Index Forecasting Scheme Based on Online News Sentiment Analysis
The real estate price index serves as a crucial indicator reflecting the operational status of the real estate market in China. However, it often lags until mid-next month, hindering stakeholders from grasping market trends in real time. Moreover, the real estate market has an extremely complex oper...
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MDPI AG
2025-01-01
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| Series: | Systems |
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| author | Tao Xu Yingying Zhao Jie Yu |
| author_facet | Tao Xu Yingying Zhao Jie Yu |
| author_sort | Tao Xu |
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| description | The real estate price index serves as a crucial indicator reflecting the operational status of the real estate market in China. However, it often lags until mid-next month, hindering stakeholders from grasping market trends in real time. Moreover, the real estate market has an extremely complex operating mechanism, which makes it difficult to accurately assess the impact of various policy and economic factors on the real estate price index. Therefore, we hope, from the perspective of data science, to explore the emotional fluctuations of the public towards the real estate market and to reveal the dynamic relationship between the real estate price index and online news sentiment. Leveraging massive online news data, we propose a forecasting scheme for the real estate price index that abandons complex policy and economic data dependence and is solely based on common and easily obtainable online news data. This scheme involves crawling historical online real estate news data in China, employing a BERT-based sentiment analysis model to identify news sentiment, and subsequently aggregating the monthly Real Estate Sentiment (RES) index for Chinese cities. Furthermore, we construct a Vector Autoregression (VAR) model using the historical RES index and housing price index to forecast future housing price indices. Extensive empirical research has been conducted in Beijing, Shanghai, Guangzhou, and Shenzhen, China, to explore the dynamic interaction between the RES index and both the new housing price index and the second-hand housing price index. Experimental results showcase the unique features of the proposed RES index in various cities and demonstrate the effectiveness and utility of our proposed forecasting scheme for the real estate price index. |
| format | Article |
| id | doaj-art-59a85f2396ba4dcba46679b1e50ab514 |
| institution | Kabale University |
| issn | 2079-8954 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
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| series | Systems |
| spelling | doaj-art-59a85f2396ba4dcba46679b1e50ab5142025-01-24T13:50:35ZengMDPI AGSystems2079-89542025-01-011314210.3390/systems13010042A Real Estate Price Index Forecasting Scheme Based on Online News Sentiment AnalysisTao Xu0Yingying Zhao1Jie Yu2School of Computer and Information Engineering, Henan University, Zhengzhou 450046, ChinaSchool of Computer and Information Engineering, Henan University, Zhengzhou 450046, ChinaSchool of College English Teaching and Research, Henan University, Zhengzhou 450046, ChinaThe real estate price index serves as a crucial indicator reflecting the operational status of the real estate market in China. However, it often lags until mid-next month, hindering stakeholders from grasping market trends in real time. Moreover, the real estate market has an extremely complex operating mechanism, which makes it difficult to accurately assess the impact of various policy and economic factors on the real estate price index. Therefore, we hope, from the perspective of data science, to explore the emotional fluctuations of the public towards the real estate market and to reveal the dynamic relationship between the real estate price index and online news sentiment. Leveraging massive online news data, we propose a forecasting scheme for the real estate price index that abandons complex policy and economic data dependence and is solely based on common and easily obtainable online news data. This scheme involves crawling historical online real estate news data in China, employing a BERT-based sentiment analysis model to identify news sentiment, and subsequently aggregating the monthly Real Estate Sentiment (RES) index for Chinese cities. Furthermore, we construct a Vector Autoregression (VAR) model using the historical RES index and housing price index to forecast future housing price indices. Extensive empirical research has been conducted in Beijing, Shanghai, Guangzhou, and Shenzhen, China, to explore the dynamic interaction between the RES index and both the new housing price index and the second-hand housing price index. Experimental results showcase the unique features of the proposed RES index in various cities and demonstrate the effectiveness and utility of our proposed forecasting scheme for the real estate price index.https://www.mdpi.com/2079-8954/13/1/42real estate price indexonline newssentiment analysisBERTVARtime series forecasting |
| spellingShingle | Tao Xu Yingying Zhao Jie Yu A Real Estate Price Index Forecasting Scheme Based on Online News Sentiment Analysis Systems real estate price index online news sentiment analysis BERT VAR time series forecasting |
| title | A Real Estate Price Index Forecasting Scheme Based on Online News Sentiment Analysis |
| title_full | A Real Estate Price Index Forecasting Scheme Based on Online News Sentiment Analysis |
| title_fullStr | A Real Estate Price Index Forecasting Scheme Based on Online News Sentiment Analysis |
| title_full_unstemmed | A Real Estate Price Index Forecasting Scheme Based on Online News Sentiment Analysis |
| title_short | A Real Estate Price Index Forecasting Scheme Based on Online News Sentiment Analysis |
| title_sort | real estate price index forecasting scheme based on online news sentiment analysis |
| topic | real estate price index online news sentiment analysis BERT VAR time series forecasting |
| url | https://www.mdpi.com/2079-8954/13/1/42 |
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