Text mining methodologies with R: An application to central bank texts

We review several existing text analysis methodologies and explain their formal application processes using the open-source software R and relevant packages. Several text mining applications to analyze central bank texts are presented.

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Year of publication:	2022
Authors:	Benchimol, Jonathan ; Kazinnik, Sophia ; Saadon, Yossi
Published in:	Machine Learning with Applications. - Amsterdam : Elsevier, ISSN 2666-8270. - Vol. 8.2022, p. 1-19
Publisher:	Amsterdam : Elsevier
Subject:	Text mining \| R programming \| Sentiment analysis \| Topic modeling \| Natural language processing \| Central bank communication \| Bank of Israel \| Text analysis \| Central bank texts \| Text cleaning

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Type of publication:	Article
Type of publication (narrower categories):	Article
Language:	English
Other identifiers:	10.1016/j.mlwa.2022.100286 [DOI] hdl:10419/323255 [Handle] RePEc:zbw:espost:323255 [RePEc]
Classification:	B40 - Economic Methodology. General ; C82 - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data ; C87 - Econometric Software ; D83 - Search, Learning, Information and Knowledge ; E58 - Central Banks and Their Policies ; E59 - Monetary Policy, Central Banking and the Supply of Money and Credit. Other
Source:	EconStor

Persistent link: https://www.econbiz.de/10015436205