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        <title>Using Word Embedding to Reveal Monetary Policy Explanation Changes</title>
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    <abstract>Documents have been an essential tool of communication for governments to announce their policy operations. Most policy announcements have taken the form of text to inform their new policies or changes to the public. To understand such policymakers’ communication, many researchers exploit published policy documents. However, the methods well-used in other research domains such as sentiment analysis or topic modeling are not suitable for studying policy communications. Their training corpora and methods are not for policy documents where technical terminologies are used, and sentiment expressions are refrained. We leverage word embedding techniques to extract semantic changes in the monetary policy documents. Our empirical study shows that the policymaker uses different semantics according to the type of documents when they change their policy.</abstract>
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    <identifier type="doi">10.18653/v1/2021.econlp-1.8</identifier>
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%0 Conference Proceedings
%T Using Word Embedding to Reveal Monetary Policy Explanation Changes
%A Matsui, Akira
%A Ren, Xiang
%A Ferrara, Emilio
%Y Hahn, Udo
%Y Hoste, Veronique
%Y Stent, Amanda
%S Proceedings of the Third Workshop on Economics and Natural Language Processing
%D 2021
%8 November
%I Association for Computational Linguistics
%C Punta Cana, Dominican Republic
%F matsui-etal-2021-using
%X Documents have been an essential tool of communication for governments to announce their policy operations. Most policy announcements have taken the form of text to inform their new policies or changes to the public. To understand such policymakers’ communication, many researchers exploit published policy documents. However, the methods well-used in other research domains such as sentiment analysis or topic modeling are not suitable for studying policy communications. Their training corpora and methods are not for policy documents where technical terminologies are used, and sentiment expressions are refrained. We leverage word embedding techniques to extract semantic changes in the monetary policy documents. Our empirical study shows that the policymaker uses different semantics according to the type of documents when they change their policy.
%R 10.18653/v1/2021.econlp-1.8
%U https://aclanthology.org/2021.econlp-1.8
%U https://doi.org/10.18653/v1/2021.econlp-1.8
%P 56-61

Markdown (Informal)

[Using Word Embedding to Reveal Monetary Policy Explanation Changes](https://aclanthology.org/2021.econlp-1.8) (Matsui et al., ECONLP 2021)

• Using Word Embedding to Reveal Monetary Policy Explanation Changes (Matsui et al., ECONLP 2021)

ACL

• Akira Matsui, Xiang Ren, and Emilio Ferrara. 2021. Using Word Embedding to Reveal Monetary Policy Explanation Changes. In Proceedings of the Third Workshop on Economics and Natural Language Processing, pages 56–61, Punta Cana, Dominican Republic. Association for Computational Linguistics.