Network text analysis of medical tourism in newspapers using text mining: The South Korea case

The main purpose of this study was to investigate keywords related to medical tourism in daily and medical newspapers and to analyze networks between keywords. We collected newspaper articles by running a web crawler with Python. A total of 3802 articles from 4 medical newspapers and 1705 articles from 5 daily newspapers from 2009 to 2017 were reviewed. The clusters derived from daily newspapers focus mainly on medical tourists, medical care and service, regional vitalization, and field support. In contrast, the clusters derived from medical newspapers focus mainly on medical tourism marketing, introducing medical treatment overseas, the medical community's voice, and medical tourism vitalization with support from a government. We found that the content varied depending on the characteristics of the newspapers. This information is necessary to understand various perspectives on policymaking. The academic contributions and practical implications of the findings are discussed.