Discovering associations in COVID-19 related research papers

• URL: http://arxiv.org/abs/2004.03397v1
• Date: Mon, 6 Apr 2020 10:52:25 GMT
• Title: Discovering associations in COVID-19 related research papers
• Authors: Iztok Fister Jr., Karin Fister, Iztok Fister
• Abstract summary: Our study analyses the abstracts of papers related to COVID-19 and coronavirus-related-research using association rule text mining. On the basis of these methods, the purpose of our study was to show how researchers have responded in similar epidemic/pandemic situations throughout history.
• Score: 2.146386506780702
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: A COVID-19 pandemic has already proven itself to be a global challenge. It proves how vulnerable humanity can be. It has also mobilized researchers from different sciences and different countries in the search for a way to fight this potentially fatal disease. In line with this, our study analyses the abstracts of papers related to COVID-19 and coronavirus-related-research using association rule text mining in order to find the most interestingness words, on the one hand, and relationships between them on the other. Then, a method, called information cartography, was applied for extracting structured knowledge from a huge amount of association rules. On the basis of these methods, the purpose of our study was to show how researchers have responded in similar epidemic/pandemic situations throughout history.

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