Abstract
In this paper, we analyzed effects of the 2011 Thai flooding on Japanese economics. In the paper, we propose, as a new time series economics data analysis method, an integrated approach of Singular Value Decomposition on stock data and news article text mining. There we first find the correlations among companies’ stock data and then in order to find the latent logical reasons of the associations, we conduct text mining. The paper shows the two-stage approach’s advantages to refine the logical reasoning. Concerning the Thai flooding effects on the Japan’s economy, as unexpected moves, we have found the serious harms on the Japanese food and drink companies and its quick recoveries.
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Acknowledgement
We thank Prof Takako Hashimoto (Chiba University of Commerce) for her wide range of knowledge about Thai economy that helps our research. This research was partly supported by funds from the Telecommunications Advancement Foundation research project in 2015 to 2016. In addition, this study was partly supported by a grant from the Japanese Society for the Promotion of Science from 2015-2017 (15K03619). We sincerely express our gratitude to the Society for its support.
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Yano, Y., Shirota, Y. (2016). SVD and Text Mining Integrated Approach to Measure Effects of Disasters on Japanese Economics. In: Hirose, A., Ozawa, S., Doya, K., Ikeda, K., Lee, M., Liu, D. (eds) Neural Information Processing. ICONIP 2016. Lecture Notes in Computer Science(), vol 9949. Springer, Cham. https://doi.org/10.1007/978-3-319-46675-0_3
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DOI: https://doi.org/10.1007/978-3-319-46675-0_3
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