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News media’s framing of health policy and its implications for government communication: A text mining analysis of news coverage on a policy to expand health insurance coverage in South Korea

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  • Jo, Wonkwang
  • You, Myoungsoon

Abstract

On August 9, 2017, South Korea announced a new measure to expand National Health Insurance (NHI) coverage, which was nicknamed “Mooncare.” At the early stage of its implementation, the interpretation of a policy by social actors influences its success and the formation of social conflicts around it. This study sought to identify the strategies for interpreting Mooncare in newspapers and government documents and examine the conflicts between them. Therefore, this study used text mining methods that are well-suited to processing large amounts of natural language data. Findings revealed that, while the conservative newspaper The Chosun Ilbo tended to highlight the financial feasibility of Mooncare, the liberal newspaper The Hankyoreh emphasized the change in rationality of government from the previous administration implied by Mooncare. Additionally, medical newspapers tended to adopt the perspective of healthcare providers and to focus on the changes in the medical system that may threaten them. In contrast, general newspapers tended to adopt the perspective of Mooncare’s beneficiaries. Finally, government documents were found to focus on simply introducing the benefits of Mooncare, not responding to the framings of various media. This study identified how various social actors interpreted Mooncare. The results suggest that the government should assume a more active role in the meaning making of the policy.

Suggested Citation

  • Jo, Wonkwang & You, Myoungsoon, 2019. "News media’s framing of health policy and its implications for government communication: A text mining analysis of news coverage on a policy to expand health insurance coverage in South Korea," Health Policy, Elsevier, vol. 123(11), pages 1116-1124.
  • Handle: RePEc:eee:hepoli:v:123:y:2019:i:11:p:1116-1124
    DOI: 10.1016/j.healthpol.2019.07.011
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    References listed on IDEAS

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    1. Margaret Roberts & Brandon Stewart & Tingley, Dustin, 2014. "stm: R Package for Structural Topic Models," Working Paper 176291, Harvard University OpenScholar.
    2. Margaret E. Roberts & Brandon M. Stewart & Dustin Tingley & Christopher Lucas & Jetson Leder‐Luis & Shana Kushner Gadarian & Bethany Albertson & David G. Rand, 2014. "Structural Topic Models for Open‐Ended Survey Responses," American Journal of Political Science, John Wiley & Sons, vol. 58(4), pages 1064-1082, October.
    3. Kim, Hongsoo & Jung, Young-Il & Kwon, Soonman, 2015. "Delivery of institutional long-term care under two social insurances: Lessons from the Korean experience," Health Policy, Elsevier, vol. 119(10), pages 1330-1337.
    4. Government of India, 2017. "National Health Policy 2017," Working Papers id:11664, eSocialSciences.
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    Cited by:

    1. Lee, Seungpeel & Kim, Jina & Kim, Dongjae & Kim, Ki Joon & Park, Eunil, 2023. "Computational approaches to developing the implicit media bias dataset: Assessing political orientations of nonpolitical news articles," Applied Mathematics and Computation, Elsevier, vol. 458(C).

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