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Title: | 媒體情緒對大台北房市之影響: 文字探勘之應用 Application of Text Mining: The Influence of Media Sentiment on Real Estate Market in Taipei Metropolitan Area |
Authors: | 黃御維 Huang, Yu-Wei |
Contributors: | 陳明吉 Chen, Ming-Chi 黃御維 Huang, Yu-Wei |
Keywords: | 網路爬蟲 文字探勘 情緒分析 媒體情緒指數 房地產市場 Web crawler Text mining Sentiment analysis Real estate market Media sentiment index |
Date: | 2019 |
Issue Date: | 2019-08-07 16:04:14 (UTC+8) |
Abstract: | 房地產市場的產品異質性高,再加上台灣房地產市場的資訊不對稱的問題嚴重,往往新聞媒體的資訊與消息成為市場參與者分析房市之重要來源,導致市場參與者較容易地受到媒體的風向影響,改變其對於房市的觀點。本研究透過網路爬蟲抓取2006年至2017年間共21,678篇有關台北市與新北市的房市與總體經濟新聞作為研究資料,透過文字探勘中的情緒分析方式,探討媒體情緒指數與房地產市場之關係,選取房價、房屋交易量、房屋流通天數與議價空間為房市狀況指標。本研究發現,不論新北市或是台北市,本研究編制的媒體情緒指數對於其房價、交易量與流通天數都是呈現顯著的影響,表示媒體對於房市的報導態度,會直接或間接地影響市場參與者之想法或預期,進而投入房地產市場,此外房市新聞報導的頻率對於房價、成交量與流通天數也有顯著的相關性,亦表示新聞報導量的增加,將會推升市場參與者對於下一期房市之預期。本研究也透過Copula動態相關分析,發現兩地區房價和交易量與其媒體情緒指數之動態相關性約在2012年時開始產生明顯變化,甚至由正相關轉為負相關,本研究認為此相關性具有明顯的變化是因為當時政府積極推動各項房市政策以抑制房價,例如:2011年奢侈稅的上路, 2012年實施豪宅限貸令與實施時價登錄,因此房市政策的實施,也會影響市場參與者的態度與房市展望。 The real estate market exist high product heterogeneity, and there also is a serious problem of information asymmetry in the Taiwan real estate market. The information and news from news media often become an important source for market participants to analyze the housing market, which makes it easier for market participants to be influenced by the media`s spin control and change their perspective on the housing market. We used web crawler to download 21,678 articles about the housing market and macroeconomics news of Taipei City and New Taipei City from 2006 to 2017. Through the method of text mining and emotional analysis, we want to explore the relationship between the media sentiment index and the real estate market, including house price, trading volume, circulation days and bargaining space. We found that regardless of New Taipei City or Taipei City, the media sentiment index of the two regions has a significant impact on their housing prices, trading volume and circulation days, indicating that the attitude of media`s reporting towards the housing market would directly or indirectly affect the ideas or expectations of market participants, and then join the real estate market. In addition, the frequency of news reporting has a significant correlation with the price, volume and circulation days. It also indicates that the increase in volume of news will boost market participants` expectations for the housing market performance in next period.We also use Copula dynamic correlation analysis and found that the dynamic correlation between house prices and media sentiment index in the two regions began to change significantly in 2012, even from positive correlation to negative correlation. We believe that this correlation has obvious changes because the government actively promoted various housing policies to curb housing prices. |
Reference: | 英文參考文獻
Anne, K., & Poteet, S. R. (2007). Natural Language Processing and Text Mining: Springer. Baker, M., & Wurgler, J. (2007). Investor Sentiment in the Stock Market. Journal of Economic Perspectives, 21(2), 129-151. Ball-Rokeach, Sandra J., & DeFleur, M. (1976). A Dependency Model of Mass Media Effects. Communication Research, 3(1), 3-21 Barber, B. M., & Odean, T. (2008). All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors. The Review of Financial Studies, 21(2), 785-818. Beracha, E., & Wintoki, M. B. (2013). Forecasting Residential Real Estate Price Changes from Online Search Activity. Journal of Real Estate Research, 35(3), 283-312. Chen, M.-C., & Patel, K. (2002). An empirical analysis of determination of house prices in the Taipei area. Taiwan Economic Review, 30(4), 563-595. Chen, M.-C., Tsai, I.-C., & Chang, C.-O. (2007). House prices and household income: Do they move apart? Evidence from Taiwan. Habitat International, 31(2), 243-256. Dong, Z., Dong, Q., & Hao, C. (2010). HowNet and its computation of meaning. Paper presented at the Proceedings of the 23rd International Conference on Computational Linguistics: Demonstrations, Beijing, China. Dougal, C., Engelberg, J., García, D., & Parsons, C. A. (2012). Journalists and the Stock Market. The Review of Financial Studies, 25(3), 639-679. Engelberg, J. E., & Parsons, C. A. (2011). The Causal Impact of Media in Financial Markets. The Journal of Finance, 66(1), 67-97. Feldman, R., & Sanger, J. (2002). The Text Mining Handbook: Cambridge University Press. Fenzl, T., & Pelzmann, L. (2012). Psychological and Social Forces Behind Aggregate Financial Market Behavior. Journal of Behavioral Finance, 13(1), 56-65. Garcia, D. (2013). Sentiment during Recessions. The Journal of Finance, 68(3), 1267-1300. Gentzkow, M., & Shapiro, J. M. (2010). What Drives Media Slant? Evidence From U.S. Daily Newspapers. Journal of the econometric society, 78(1), 35-71. Godbole, N., Srinivasaiah, M., & Skiena, S. (2007). Large- Scale Sentiment Analysis for News and Blogs. ICWSM, 7(21), 219-222. Granziera, E., & Kozicki, S. (2015). House price dynamics: Fundamentals and expectations. Journal of Economic Dynamics and Control, 60, 152-165. Hanley, K. W., & Hoberg, G. (2010). The Information Content of IPO Prospectuses. The Review of Financial Studies, 23(7), 2821-2864. Hong, H., & Stein, J. C. (2007). Disagreement and the Stock Market. Journal of Economic Perspectives, 21(2), 109- 128. Hu, M., & Liu, B. (2004). Mining Opinion Features in Customer Reviews Proceedings of the 19th National Conference on Artificial Intelligence, 755-776. Hui, E. C. M., Dong, Z., Jia, S., & Lam, C. H. L. (2017). How does sentiment affect returns of urban housing? Habitat International, 64, 71-84. Keynes, J. M. (1936). The General Theory of Employment, Interest and Money. Palgrave Macmillan. Ku, L.-W., Lo, Y.-S., & Chen, H.-H. (2007). Using polarity scores of words for sentence-level opinion extraction. Paper presented at the Proceedings of NTCIR-6 workshop meeting, Tokyo, Japan. Lai, R. N., & Order, R. A. V. (2010). Momentum and House Price Growth in the United States: Anatomy of a Bubble. Real Estate Economics, 38(4), 753-773. Lambertini, L., Mendicino, C., & Punzi, M. T. (2013). Expectation-driven cycles in the housing market: Evidence from survey data. Journal of Financial Stability, 9(4), 518-529. Liu, B. (2012). Sentiment Analysis and Opinion Mining (Vol. 5): Morgan & Claypool Publishers. Loughran, T., & Mcdonald, B. (2011). When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10 ‐Ks. The Journal of Finance, 66(1), 35-65. Loughran, T., & Mcdonald, B. (2014). Measuring Readability in Financial Disclosures. The Journal of Finance, 69(4), 1643-1671. Marcato, G., & Nanda, A. (2016). Information Content and Forecasting Ability of Sentiment Indicators: Case of Real Estate Market. Journal of Real Estate Research, 38(2), 165-203. Medhat, W., Hassan, A., & Korashy, H. (2014). Sentiment analysis algorithms and applications: A survey. Ain Shams Engineering Journal, 5(4), 1093-1113. Meen, G. P. (1990). The removal of mortgage market constraints and the implications for econometric modelling of UK house prices, Oxford Bulletin Economics and Statistics, 52 (1):1-23. Mikhed, V., & Zemčík, P. (2009). Do house prices reflect fundamentals? Aggregate and panel data evidence. Journal of Housing Economics, 18(2), 140-149. Mäntylä, M. V., Graziotin, D., & Kuutila, M. (2018). The evolution of sentiment analysis—A review of research topics, venues, and top cited papers. Computer Science Review, 27, 16-32. Peress, J. (2014). The Media and the Diffusion of Information in Financial Markets: Evidence from Newspaper Strikes. The Journal of Finance, 69(5). Ren, Y., & Yuan, Y. (2012). Why the Housing Sector Leads the Whole Economy: The Importance of Collateral Constraints and News Shocks. The Journal of Real Estate Finance and Economics, 48(2), 323-341. Scott, L. O. (1990). Do prices reflect market fundamentals in real estate markets? The Journal of Real Estate Finance and Economics, 3(1), 5-23. Shiller, R. J. (2000). Irrational Exuberance. Philosophy and Public Policy Quarterly, 20(1), 18-23. Shiller, R. J. (2005). Irrational Exuberance. Princeton: NJ: Princeton University Press. Shiller, R. J., & Akerlof, G. A. (2010). Animal Spirits. Princeton: NJ: Princeton University Press. Soo, C. K. (2018). Quantifying Sentiment with News Media across Local Housing Markets. The Review of Financial Studies, 31(10), 3689-3719. Sullivan, D. (2001). Document Warehousing and Text Mining: Techniques for Improving Business Operations, Marketing, and Sales: John Wiley & Sons, Inc. New York, NY, USA ©2001. Tan, A.-H. (1999). Text mining: Promises and challenges. Paper presented at the Proceedings south east Asia research computer confederation (SEARCC99), Singapore City, Singapore. Tetlock, P. C. (2007). Giving Content to Investor Sentiment: The Role of Media in the Stock Market. The Journal of Finance, 62(3). Tetlock, P. C., Saar‐Tsechansky, M., & Macskassy, S. (2008). More Than Words: Quantifying Language to Measure Firms` Fundamentals. The Journal of Finance, 63(3), 1437-1467. Walker, C. B. (2014). Housing booms and media coverage. Applied Economics, 46(32), 3954-3967.
中文參考文獻
吳森田. (1994). 所得、貨幣與房價——近二十年台北地區的觀察. 住宅 學報, 2, 49-65. 李政儒, 游基鑫, & 陳信希. (2012). 廣義知網詞彙意見極性的預測. 中文計算語言學期刊, 17(2), 21-36. 李美杏, 陳威廷, & 彭建文. (2014). 亞洲城市房價基值與泡沫. 都市 與計劃, 41(2), 169-198. 林宜萱. (2013). 財經領域情緒辭典之建置與其有效性之驗證-以財經新 聞為元件. (碩士), 臺灣大學會計學研究所. 林秋瑾, 王健安, & 張金鶚. (1997). 房地產景氣與總體經濟景氣於時 間上領先、同時、落後關係之探討. 國家科學委員會彙刊;人文及社 會科學, 7(1), 35-56. 張津挺. (2015). 中文財務情緒字典建構與其在財務新聞分析之應用. (碩士), 臺北市立大學資訊科學系. 彭建文, & 張金鶚. (2000). 總體經濟對房地產景氣影響之研究. 國家 科學委員會研究彙刊:人文及社會科學, 10(3), 330-343. 廖慧玲. (2011). 貨幣供給、新台幣匯率對房價指數與股價報酬率關聯性 之研究. (碩士在職專班), 國立臺北大學國際財務金融碩士在職專 班. 趙鵬, 趙志偉, & 卓景文. (2011). 一種情感詞語意加權的句子傾向性 識別方法. 計算機工程與應用, 47(35), 161-163. 蔡怡純, & 陳明吉. (2013). 房價之不對稱均衡調整:門檻誤差修正模 型應用. 臺灣土地研究, 16(1), 37-58. 鍾任明, 李維平, & 吳澤民. (2007). 運用文字探勘於日內股價漲跌趨 勢預測之研究. 中華管理評論國際學報, 10(1). |
Description: | 碩士 國立政治大學 財務管理學系 106357018 |
Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0106357018 |
Data Type: | thesis |
DOI: | 10.6814/NCCU201900185 |
Appears in Collections: | [財務管理學系] 學位論文
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