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https://nccur.lib.nccu.edu.tw/handle/140.119/158022
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| Title: | 社群觀測資料之文字探勘：房市與投資人心理之研究
Text Mining on the Social Media Data: an Analysis of the Real Estate Market and Investor Psychology |
| Authors: | 朱芳妮 |
| Contributors: | 地政系 |
| Keywords: | 社群觀測資料;文字探勘;有限關注;心理偏誤;不動產市場;投資者心理
social media data;text mining;limited attention;psychological bias;real estate market;investor psychology |
| Date: | 2022-10 |
| Issue Date: | 2025-07-14 11:11:04 (UTC+8) |
| Abstract: | 不動產市場變化會衝擊經濟發展，若能瞭解投資人如何決策即可掌握市場動態。本研究使用文字探勘方法在社群觀測資料上萃取資訊來建置投資人關注指標，藉此瞭解投資人決策依據，及其對於房市動態之影響。不僅在學術上可驗證行為經濟理論應用在房市研究之適宜性，在實務上亦可供投資人、產業投資決策與政府政策研擬之參考。
People are often not able to make full use of information to make the most appropriate decision, because people have limited ability to process large amounts of information, and attention to large amounts of information must be limited and selective. After Merton (1987) proposed investor recognition hypothesis, "investors' limited attention" has become an important direction for research in recent years. This project will conduct a series of research on the limited attention of investors. We collect data from social observation media and use text mining technique. The first year project uses text mining technique to extract social observation data to establish investor attention indicators to test whether the attention will lead to price discovery. In addition, based on the investor's recognition hypothesis, we test whether the investor's attention to new and existing housing prices are different. We will also compare the accuracy of different indicators of interest in predicting house prices. The second year is based on the theory of psychological bias. Investors of different ethnic groups should have different concerns. Therefore, we test whether investors of different ethnic groups have category learning behaviors and analyze whether they have different effects on the housing price, volume, sales period, and bargaining space. In the third year, the project focused on the asymmetry of investors ’attention, such as the positive or negative sentiment, and the asymmetry of changes in the housing market, such as the rise or fall of investors’ concerns. This project continues the previous project, but the difference lies in the use of text exploration technology in social observation data, and further analysis of the housing market in term of sales period and bargaining space that cannot be obtained in the past research. Analysis of different investment groups, and analysis of asymmetric psychology and market asymmetry are engaged. This project has moved forward more significantly than previous project. Our results will help to understand the psychology of investors and explain the changes in the market, and also provide a reference for the government on real estate policies. |
| Relation: | 科技部,MOST109-2410-H004-194-MY2, 109.08-111.07 |
| Data Type: | report |
| Appears in Collections: | [地政學系] 國科會研究計畫
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