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Procedia Computer Science
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Procedia Computer Science
Article
License: CC BY NC ND
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Procedia Computer Science
Article . 2020
License: Elsevier TDM
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Mining text on Coronavirus

Authors: Cristian O. Beltrán-Oicatá; Mercedes Gaitán-Angulo; Melissa Lis-Gutiérrez; Alexa Senior Naveda;

Mining text on Coronavirus

Abstract

Abstract This document describes the behavior of the production of academic papers and high circulation newspapers, published under the terms “Coronavirus, Covid-19 or SARS-CoV-2”. The purpose of this paper is to employ text mining techniques and qualitative data analysis for pattern identification (Dobrzynski, Dziekonski, Krzysztof, & Jurczuk, 2013; Westergaard, Staerfeldt, Tonsberg, Jensen, & Brunak, 2018). The interest of this study arises from the importance of this topic today and its relationship with the economy, business and society. As a result, the production of scientific papers has been led by the United States, China and Russia. In Latin America, Brazil is the country with the highest scientific output on this subject. The analysis of newspaper articles focusing on economic and business issues showed the work between large companies, the government and the community, as well as companies with businesses and the need to adapt to constant change in the face of the crisis of labor and production.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold