npsm 새물리 New Physics : Sae Mulli

pISSN 0374-4914 eISSN 2289-0041


Research Paper

New Physics: Sae Mulli 2017; 67: 548-554

Published online May 31, 2017

Copyright © New Physics: Sae Mulli.

Text Network Analysis of Financial Information for Consumer Decision-Making

Kyungyoung OHK1, Miyea KIM*2, Kayeong KIM1

1 Department~of Consumer Economics, Sookmyung Women’s University, Seoul 04310, Korea

2 Research Institute of ICT Convergence, Sookmyung Women’s University, Seoul 04310, Korea


Received: January 10, 2017; Revised: March 16, 2017; Accepted: March 16, 2017

This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.


Recently, insufficient information has led to consumer health-insurance duplication. This study determines which financial information is essential to consumer decision-making. Consumers’ health-insurance consultations were analyzed in three stages of decision-making (pre-enrollment, enrollment, and post-enrollment) through text mining and text network analysis. Higher frequency words were identified for each of the three stages. For example, these included “inquiry” and “fee-for-service health” at pre-enrollment; “indemnity health insurance” and “insurance agent” at the time of enrollment; and “claim,” “compensation,” and “benefits” after enrollment. Also, centrality of the text network analysis identified the terms that were located centrally on a graph in each of the three stages. Results confirmed that different information is required for each decision-making stages.

Keywords: Text mining, Text network analysis, Consumer decision-making, Financial information, Indemnity health insurance

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