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http://dx.doi.org/10.14400/JDC.2019.17.9.047

A Study on the Polarity of Apartment Price News Using Big Data Analysis Method  

Cho, Sang-Yeon (Department of Real Estate, The Graduate School, Sangmyung University)
Hong, Eun-Pyo (Department of Economics and Finance, Sangmyung University)
Publication Information
Journal of Digital Convergence / v.17, no.9, 2019 , pp. 47-54 More about this Journal
Abstract
This study confirms the polarity of news articles on apartment prices using Opinion Mining which has widely been used for a big data analysis. The analyses were carried out utilizing internet news articles posted on the Naver for two years: 2012 and 2018. We proposed a sentiment analysis model and modeled a topic-oriented sentiment dictionary construction methods. As a result of analyzing the proposed sentiment analysis model, it was confirmed that there was a difference according to the tendency of the media companies in selecting social issues at the time of rising apartment prices. At the same time, we were able to find more affirmative articles in the media companies which share similar sentiment with the government in charge. In this paper, we proposed a sentiment analysis model that can be used in real estate field and analyzed the polarity of unformatted data related to real estate. In order to integrate them into various fields in the future, it is necessary to build the sentiment dictionaries by themes, as well as to collect various unformatted data over extended periods.
Keywords
Real Estate; Apartment Big Data; Opinion Mining; Sentiment Analysis Model;
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Times Cited By KSCI : 4  (Citation Analysis)
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1 N. D. Kim. (2018). Trend Korea 2019. Seoul : The Window of Future.
2 Korea Development Bank. (2016. Oct). The Rise of Big Data Industry and Implications. Monthly KDB Survery Report, 731, 82-102.
3 Korea Development Bank. (2017. Sep). Change The Trend of The Real Estate Market with Big Data. Weekly KDB Report, Issue Brief, 8-11.
4 J. I. Kyung. (2014). Big Data Utilization Scheme of The Real Estate Sector and Policy Recommendations. Journal of The Korea Real Estate Management, 10, 65-67.
5 W. Paik, M. H. Kyoung, K. S. Min, H. R. Oh, C. Lim & M. S. Shin. (2007). Multi-Stage News Classification System for Predicting Stock Price Changes. Journal of The Korean Society for Information Management, 24(2), 123-141.   DOI
6 J. I. Kyung & K. C. Lee. (2016). Development of Sentiment Analysis of Real Estate Big data by Using Textmining. Housing Studies Review, 24(4), 115-136.
7 Y. S. Kim. (2012). News Big Data Opinion Mining Model for Predicting KOSPI Movement. Doctoral Dissertation. Kookmin University, Seoul.
8 S. H. Yang. (2012). The Changing News Framing in Korean Journalism -Focused on Comparing The Reports about KORUS FTA on The Chosun Ilbo, The Seoul Shinmun and The Hankyoreh. Doctoral Dissertation. Sungkunkwan University, Seoul.
9 Wilson, Theresa, Janyce Wiebe & Rebecca Hwa. (2004). Just how mad are you? Finding Strong and Weak Opinion. aaai, 4.
10 Esuli, Andrea & F. Sebasttiani. (2005). Determining The Semantic Orientation of Terms through Gloss Classification. ACM.
11 E. J. Yu, Y. S. Kim, N. G. Kim & S. R. Jeong. (2013). Predicting The Direction of The Stock Index by Using a Domain-Specific Sentiment Dictionary. Korea Intelligent Information Systems Society, 19(1), 95-110.   DOI
12 K. B. Kim. (2016). News Big Data Opinion Mining Model for Predicting KOSPI Movement. Doctoral Dissertation. Soongsil University, Seoul.
13 J. H. LEE. (2018). Cambridge Analytical Scandal Over Facebook. Economy Chosun, 245.
14 Korea Appraisal Board. (2019. Feb). Transaction-Based Price Indices for The Multi-Unit Housing Market, 116072, 1-2.
15 W. S. Kim, J. H. Lee, J. W. Park & J. H. Choi. (2014). A Technique of The Approval Rating Analysis for Political Party Using Opinion Mining. Korean Institute of Information Technology, 12(10), 133-141.
16 Y. N. Lee, E. J. Choi & M. J. Kim. (2018). Analysis of The Influence of Presidential Candidate's SNS Reputation on Election Result: Focusing on 19th Presidential Election. Journal of Digital Convergence, 16(2), 195-201.   DOI
17 S. W. Kim & N. K. Kim. (2013). A Study on The Effect of Using Sentiment Lexicon, Korea Intelligent Information Systems Society, 121-128.
18 Y. B. Cho, S. H. Woo & S. H. Lee. (2013). In Small and Medium Business the Government 3.0-based Big Data Utilization Policy. Journal of Convergence for Information Technology, 3(1), 15-22.
19 M. H. Jang & H. S. Kim. (2019). A Research on Fluctuations of Housing Prices Using Text Mining. Journal of The Korea Housing Association, 30, 35-42.   DOI
20 J. C. Choi. (2018). Big Data Patent Analysis Using Social Network Analysis. Journal of the Korea Convergence Society, 9(2), 251-257.   DOI