Text Mining Methodologies with R: An Application to Central Bank Texts

Benchimol, Jonathan; Kazinnik, Sophia; Saadon, Yossi

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Text Mining Methodologies with R: An Application to Central Bank Texts

Machine Learning with Applications, Elsevier, vol. 8, no. 100286, June 2022.

19 Pages Posted: 9 Aug 2023 Last revised: 13 Aug 2023

See all articles by Jonathan Benchimol

Sophia Kazinnik

Federal Reserve Banks - Quantitative Supervision & Research

Yossi Saadon

Bank of Israel - Research Department

Date Written: June 1, 2022

Abstract

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.

Note:

This work is licensed under a Creative Commons Attribution 4.0 International License.

Keywords: Text mining, R programming, Sentiment analysis, Topic modelling, Natural language processing, Central bank communication, Bank of Israel.

JEL Classification: B40, C82, C87, D83, E58.

Suggested Citation: Suggested Citation

Benchimol, Jonathan and Kazinnik, Sophia and Saadon, Yossi, Text Mining Methodologies with R: An Application to Central Bank Texts (June 1, 2022). Machine Learning with Applications, Elsevier, vol. 8, no. 100286, June 2022., Available at SSRN: https://ssrn.com/abstract=4533650