The interconnectedness of the economic content in the speeches of the US Presidents

Matteo Cinelli (), Valerio Ficcadenti () and Jessica Riccioni ()
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Matteo Cinelli: CNR-ISC
Valerio Ficcadenti: University of Macerata
Jessica Riccioni: University of Macerata

Annals of Operations Research, 2021, vol. 299, issue 1, No 26, 593-615

Abstract: Abstract The speeches stated by influential politicians can have a decisive impact on the future of a country. In particular, the economic content of such speeches affects the economy of countries and their financial markets. For this reason, we examine a novel dataset containing the economic content of 951 speeches stated by 45 US Presidents from George Washington (April 1789) to Donald Trump (February 2017). In doing so, we use an economic glossary carried out by means of text mining techniques. The goal of our study is to examine the structure of significant interconnections within a network obtained from the economic content of presidential speeches. In such a network, nodes are represented by talks and links by values of cosine similarity, the latter computed using the occurrences of the economic terms in the speeches. The resulting network displays a peculiar structure made up of a core (i.e. a set of highly central and densely connected nodes) and a periphery (i.e. a set of non-central and sparsely connected nodes). The presence of different economic dictionaries employed by the Presidents characterize the core-periphery structure. The Presidents’ talks belonging to the network’s core share the usage of generic (non-technical) economic locutions like “interest” or “trade”. While the use of more technical and less frequent terms characterizes the periphery (e.g. “yield”). Furthermore, the speeches close in time share a common economic dictionary. These results together with the economics glossary usages during the US periods of boom and crisis provide unique insights on the economic content relationships among Presidents’ speeches.

Keywords: Glossary of economics; Text mining; US Presidents’ speeches; Network analysis; Clustering (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s10479-019-03372-2

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