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Using Sentiment Analysis to Explore the Association Between News and Housing Prices

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Intelligent Information and Database Systems (ACIIDS 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10192))

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Abstract

In recent years, semi-structured and unstructured data have received substantial attention. Previous studies on sentiment analysis and opinion mining have indicated that media information features sentiment factors that can affect investor decisions. However, few studies have explored the correlation between news sentiment and housing prices; hence, the present study was conducted to investigate this correlation. A method was proposed to collect and filter news information and analyze the correlation between news sentiment and housing prices. The results indicate that news sentiment can serve as a reference for evaluating housing price trends.

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Notes

  1. 1.

    http://www.wjh.harvard.edu/~inquirer/homecat.htm.

  2. 2.

    http://www3.nd.edu/~mcdonald/Word_Lists.html.

  3. 3.

    http://kmw.chinatimes.com/.

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Acknowledgement

This research is supported by NSC 102-2627-E-004-001, MOST 103-2627-E-004-001, MOST 104-2627-E-004-001, MOST 105-2811-H-004-035.

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Authors and Affiliations

  1. Department of Accounting, College of Commerce, National Chengchi University, Taipei City, 11605, Taiwan (R.O.C.)

    Hsiao-Fang Yang & Jia-Lang Seng

Authors
  1. Hsiao-Fang Yang
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  2. Jia-Lang Seng
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Correspondence to Jia-Lang Seng .

Editor information

Editors and Affiliations

  1. Wrocław University of Science and Technology, Wroclaw, Poland

    Ngoc Thanh Nguyen

  2. Japan Advanced Institute of Science and Technology, Nomi, Japan

    Satoshi Tojo

  3. Japan Advanced Institute of Science and Technology, Nomi, Japan

    Le Minh Nguyen

  4. Wrocław University of Science and Technology, Wroclaw, Poland

    Bogdan Trawiński

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Yang, HF., Seng, JL. (2017). Using Sentiment Analysis to Explore the Association Between News and Housing Prices. In: Nguyen, N., Tojo, S., Nguyen, L., Trawiński, B. (eds) Intelligent Information and Database Systems. ACIIDS 2017. Lecture Notes in Computer Science(), vol 10192. Springer, Cham. https://doi.org/10.1007/978-3-319-54430-4_17

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  • DOI: https://doi.org/10.1007/978-3-319-54430-4_17

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