Budget Amount *help |
¥4,550,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥1,050,000)
Fiscal Year 2018: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2017: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2016: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
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Outline of Final Research Achievements |
We examined whether the natural language processing using monetary policy documents could be detect changes in the stance of policy makers. In this study, we showed that changes in monetary policy stance can be detected mostly well using two methods, latent semantic analysis (LSA) and latent Dirichlet allocation (LDA). This research shows that it is possible to extract information on policy stance by using statistical natural language processing from monetary policy related documents.
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