• Journal of Intelligence and Information Systems
• /
• v.25 no.3
• /
• pp.63-88
• /
• 2019

The goal of this paper is to investigate changes in North Korea's domestic and foreign policies through automated text analysis over North Korea represented in South Korean mass media. Based on that data, we then analyze the status of text mining research, using a text mining technique to find the topics, methods, and trends of text mining research. We also investigate the characteristics and method of analysis of the text mining techniques, confirmed by analysis of the data. In this study, R program was used to apply the text mining technique. R program is free software for statistical computing and graphics. Also, Text mining methods allow to highlight the most frequently used keywords in a paragraph of texts. One can create a word cloud, also referred as text cloud or tag cloud. This study proposes a procedure to find meaningful tendencies based on a combination of word cloud, and co-occurrence networks. This study aims to more objectively explore the images of North Korea represented in South Korean newspapers by quantitatively reviewing the patterns of language use related to North Korea from 2016. 11. 1 to 2019. 5. 23 newspaper big data. In this study, we divided into three periods considering recent inter - Korean relations. Before January 1, 2018, it was set as a Before Phase of Peace Building. From January 1, 2018 to February 24, 2019, we have set up a Peace Building Phase. The New Year's message of Kim Jong-un and the Olympics of Pyeong Chang formed an atmosphere of peace on the Korean peninsula. After the Hanoi Pease summit, the third period was the silence of the relationship between North Korea and the United States. Therefore, it was called Depression Phase of Peace Building. This study analyzes news articles related to North Korea of the Korea Press Foundation database(www.bigkinds.or.kr) through text mining, to investigate characteristics of the Kim Jong-un regime's South Korea policy and unification discourse. The main results of this study show that trends in the North Korean national policy agenda can be discovered based on clustering and visualization algorithms. In particular, it examines the changes in the international circumstances, domestic conflicts, the living conditions of North Korea, the South's Aid project for the North, the conflicts of the two Koreas, North Korean nuclear issue, and the North Korean refugee problem through the co-occurrence word analysis. It also offers an analysis of South Korean mentality toward North Korea in terms of the semantic prosody. In the Before Phase of Peace Building, the results of the analysis showed the order of 'Missiles', 'North Korea Nuclear', 'Diplomacy', 'Unification', and ' South-North Korean'. The results of Peace Building Phase are extracted the order of 'Panmunjom', 'Unification', 'North Korea Nuclear', 'Diplomacy', and 'Military'. The results of Depression Phase of Peace Building derived the order of 'North Korea Nuclear', 'North and South Korea', 'Missile', 'State Department', and 'International'. There are 16 words adopted in all three periods. The order is as follows: 'missile', 'North Korea Nuclear', 'Diplomacy', 'Unification', 'North and South Korea', 'Military', 'Kaesong Industrial Complex', 'Defense', 'Sanctions', 'Denuclearization', 'Peace', 'Exchange and Cooperation', and 'South Korea'. We expect that the results of this study will contribute to analyze the trends of news content of North Korea associated with North Korea's provocations. And future research on North Korean trends will be conducted based on the results of this study. We will continue to study the model development for North Korea risk measurement that can anticipate and respond to North Korea's behavior in advance. We expect that the text mining analysis method and the scientific data analysis technique will be applied to North Korea and unification research field. Through these academic studies, I hope to see a lot of studies that make important contributions to the nation.

• Korea Journal of Hospital Management
• /
• v.5 no.1
• /
• pp.176-199
• /
• 2000

This study is to identify factors affecting public relations(PR) activities through newspapers among hospitals. 53 acute hospitals with more than fill beds were surveyed by telephone interview, and hospital-related articles on 4 major daily newspapers were searched in KINDS(Korea Intergrated Newspapers Database System). Hospitals' PR scores were evaluated by weighting the directoin and the number of hospitals mentioned in an articles. The scores were analysed as the outcome of PR activities by some general characteristics. The mean of PR score was 4.64, most hospitals(22, 41.5%) fell on the group scored more than 0 and less than 5. Hospitals with score under zero were 7(13.2%) and the hospitals scored over 20 point were 3(5.8%). The number of beds and area, two general characteristics of hospitals, had decisive effect on PR activities. Analysis showed hospitals over 1000 beds scored 17.06 point and this group accounted for the highest. Hospitals from 600 to 799 beds scored 2.86, with 800 to 999beds scored 1.93 and with 500 to 599 beds scored 0.59. Along with area, hospitals in Seoul scored 11.50 point, in Kyong-Ki and Incheon scored 1.50 and in the other areas scored -0.23 point. Department for PR and the number of workers in PR activities made hospitals active in PR. Hospitals with PR department scored 7.05 point, without PR department scored 0.98. Hospitals with workers who is whole responsibility over 5 scored 13.67, from 3 to 4 scored 6.54, from 1 to 2 scored 1.02, and the hospitals without workers who is whole responsibility scored 0.53. Among the characteristics related with PR activities, the assignment of a report in individual hospital had significant effect on the outcome of PR. Hospitals with assigned reporters scored 8.31 point, without them scored 1.89. Finally, the factors affecting PR score were identified by multiple regression analysis. The number of beds and the area(Seoul) were significantly associated with the score in positive direction.

• Journal of Society of Occupational Therapy for the Aged and Dementia
• /
• v.12 no.2
• /
• pp.67-74
• /
• 2018

Objective : The purpose of this study is to quantitatively analyze the role of occupational therapy in long - term care insurance for the elderly using text mining, one of the big data analysis techniques. Method : For the analysis of newspaper articles, "Long - Term Care Insurance for the Elderly + Occupational Therapy for the Elderly" was collected after the period from 2007 to 208. Naver, which has a high share of the domestic search engine, utilized the database of Naver News by utilizing Textom, a web crawling tool. After collecting the article title and original text of 510 news data from the collection of the elderly long term care insurance + occupational therapy search, we analyzed the article frequency and key words by year. Result : In terms of the frequency of articles published by year, the number of articles published in 2015 and 2017 was the highest with 70 articles (13.7%), and the top 10 terms of the key word analysis showed the highest frequency of 'dementia' (344) In terms of key words, dementia, treatment, hospital, health, service, rehabilitation, facilities, institution, grade, elderly, professional, salary, industrial complex and people are related. Conclusion : In this study, it is meaningful that the textual mining technique was used to more objectively confirm the social needs and the role of the occupational therapist for the dementia and rehabilitation in the related key keywords based on the media reporting trend of the elderly long - term care insurance for 11 years. Based on the results of this study, future research should expand research field and period and supplement the research methodology through various analysis methods according to the year.