Journal of Natural Language Processing
Online ISSN : 2185-8314
Print ISSN : 1340-7619
ISSN-L : 1340-7619
Technical Report (Peer-Reviewed)
Sentiment Dictionary for Business Cycle Analysis and its Applications
Keiichi GoshimaMototsugu ShintaniHiroya Takamura
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2022 Volume 29 Issue 4 Pages 1233-1253

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Abstract

In this study, we construct a sentiment dictionary for the macroeconomic domain and present its applications. Our dictionary contains words selected by several economists from a corpus of newspaper articles on topics related to the economy. This was supplemented with additional words by using supervised learning. We use our sentiment dictionary to construct a daily business cycle index designed to capture the current state of the economy in a timely manner.

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© 2022 The Association for Natural Language Processing
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