• Journal of Practical Agriculture & Fisheries Research
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• v.22 no.2
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• pp.99-114
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• 2020

In this study we examined the topic analysis and correlation analysis by text mining from the self introduction letter of freshman at Korea National College of Agriculture and Fisheries(KNCAF) in 2020. The analysis items of the 3rd question were and the 4th question were the motivation for applying to college, the academic plan and the career plan. The text mining to the 3rd question showed that the frequency of 'friends' was overwhelmingly high, followed by keywords such as 'thought', 'time', 'opinion', 'activity', and 'club'. In the 4th question, keyword frequency such as 'thought', 'agriculture', 'KNCAF', 'farm', 'father' was high. The result of association rules analysis for each question showed that the relationship with the highest support level, which means the frequency and importance of the rule, was the {friend} <=> {thought}, {thought} <=> {KNCAF}. The confidence level of a correlation between keywords was the highest in the rules of {teacher}=>{friend}, {agriculture, KNCAF}=>{thought}. Also the lift level that indicates the closeness of two words was the highest in the rules of {friend} <=> {teacher}, {knowledge} <=> {professional}. These keywords are found to play a very important roles in analyzing betweenness centrality and analyzing degree centrality between keywords. The results of frequency analysis and association analysis were visualized with word cloud and correlation graphs to make it easier to understand all the results.

• Journal of Digital Convergence
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• v.16 no.7
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• pp.35-45
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• 2018

Research on the establishment of new governance aimed at efficient policy planning and the implementation thereof by the government has been conducted in response to social changes. Nonetheless, governance is comprehensive and encompasses different meanings; it takes various forms in the process of its actual application. Therefore, systematic classification of research on governance and analysis on its research trend are required. Accordingly, three researchers who majored in policy sciences, business informatics, and library and information science, respectively, searched for theses related to governance published since 2016 from Research Information Sharing Service and conducted a social network analysis (SNA) on them. According to their research results, the main research topics were largely classified into collaborative governance and local governance. Keywords throughout the topics included network, participation, conflict, and trust in line with the characteristics of governance. Representative subjects of governance included education, urban regeneration, and the environment. Further, measurement of betweenness centrality showed local governance was a main topic for convergent research. This study will lead to a greater understanding of research on governance and help activate such research. One limitation of this study is that it analyzed only theses with the keywords but not all theses on governance. Follow-up research should analyze all theses on governance and statistically verify them with SNA indexes.

• Korean Journal of Ecology and Environment
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• v.48 no.3
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• pp.195-202
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• 2015

We identified research trends for freshwater exotic species in South Korea using text mining methods in conjunction with bibliometric analysis. We searched scientific and common names of freshwater exotic species as searching keywords including 1 mammal species, 3 amphibian-reptile species, 11 fish species, 2 aquatic plant species. A total of 245 articles including research articles and abstracts of conference proceedings published by 56 academic societies and institutes were collected from scientific article databases. The search keywords used were the common names for the exotic species. The $20^{th}$ century (1900's) saw the number of articles increase; however, during the early $21^{st}$ century (2000's) the number of published articles decreased slowly. The number of articles focusing on physiological and embryological research was significantly greater than taxonomic and ecological studies. Rainbow trout and Nile tilapia were the main research topic, specifically physiological and embryological research associated with the aquaculture of these species. Ecological studies were only conducted on the distribution and effect of large-mouth bass and nutria. The ecological risk associated with freshwater exotic species has been expressed yet the scientific information might be insufficient to remove doubt about ecological issues as expressed by interested by individuals and policy makers due to bias in research topics with respect to freshwater exotic species. The research topics of freshwater exotic species would have to diversify to effectively manage freshwater exotic species.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.4
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• pp.408-414
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• 2018

Various studies have been conducted to reduce marine accidents. However, research on marine incidents is only marginal. There are many reports of marine incidents, but the main content of existing studies has been qualitative, which makes quantitative analysis difficult. However, quantitative analysis of marine accidents is necessary to reduce marine incidents. The purpose of this paper is to analyze marine incident data quantitatively by applying big data techniques to predict marine incident trends and reduce marine accident. To accomplish this, about 10,000 marine incident reports were prepared in a unified format through pre-processing. Using this preprocessed data, we first derived major keywords for the Marine incidents at sea using text mining techniques. Secondly, time series and cluster analysis were applied to major keywords. Trends for possible marine incidents were predicted. The results confirmed that it is possible to use quantified data and statistical analysis to address this topic. Also, we have confirmed that it is possible to provide information on preventive measures by grasping objective tendencies for marine incidents that may occur in the future through big data techniques.

• Journal of Korean Library and Information Science Society
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• v.50 no.1
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• pp.333-356
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• 2019

Open access has emerged as an alternative to overcome the crisis brought by scholarly communication on commercial publishers. The purpose of this study is to suggest the intellectual structure that reflects the newest research trend in the field of open access, to identify how the subject area is structured by using co-word analysis, and compare and analyze with the existing study. In order to do this, the total number of dataset was 761 papers collected from Web of Science during the period from January 2012 to November 2018 using information science and 2,321 keywords as a noun phase are extracted from titles and abstracts. To analyze the intellectual structure of open access, 13 topic clusters are extracted by network analysis and the keywords with higher centrallity are drawn by visualizing the intellectual relationship. In addition, after clustering analysis, the relationship was analyzed by plotting the result on the multidimensional scaling map. As a result, it is expected that our research helps the research direction of open access for the future.

• The Journal of the Korea Contents Association
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• v.18 no.4
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• pp.636-652
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• 2018

This study is about applying the concept of moral injury in reinterpreting and understanding the experience of female North Korean refugees who have experienced psychological trauma and are struggling with adjusting in their everyday lives. The database KISS and DBpia were used to search for academic peer-reviewed articles published before August 13th in 2017, using 'female or women North Korean,' 'female or women relocated North Korean,' and 'female or women North Korean defector' as keywords. In total 51 studies were finally selected for content analysis and the result were the following. First, listing from the most often occurring study topic to the least occurring topic in order: post-defection adjustment related, mothering experience, experience of North Korean regime and Korean War, work or job or employment related, recovering from psychological trauma as well as growth and resilience related, experiences in China, trauma and psychological difficulties, anxiety treatment process and effects. Second, words related to psychological aspect of moral injury appeared 260 times in 51 selected studies, changes in the existential belief appeared 82 times, cognitive aspects of moral injury appeared 71 times, and behavioral aspects 21 times. Third, two main contexts emerged to be the antecedent that led to moral injury and they were 'identity denial' and 'dismantled family.' In attempts to find opposite cases or stories where aspects of moral injury were not found despite the existence of its antecedents and it was 'identity restructuring.' Based on the finding, practice implications that could help female North Korean refugees prevent or recover from moral injury were suggested.

• Journal of Digital Convergence
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• v.19 no.10
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• pp.469-489
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• 2021

This study explores consumers' responses to socially assistive robotics by using text-mining method focusing on Companion Pets from Hasbro as it gives emotional support. We conducted text frequency analysis, LDA analysis using R programming. The key findings are 1)the most frequently used words the mimicry of living pets and the appearance of companion pets, 2)the five topics were derived from the LDA analysis and classified keywords in each topic split between positive and negative, 3)user, product, environment affect the interaction between consumer and companion pets, 4)consumers who have difficulty in cognition and physical conditions use companion pets to replace living pets. This study provides an understanding of consumer responses in companion pets and gives practical implications that may improve the efficacy of usage for consumers and understand the companion robot, which provides emotional support in COVID-19.

• The Journal of Society for e-Business Studies
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• v.26 no.2
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• pp.123-141
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• 2021

As the dependence of technology on the economic structure increases, the importance of National Core Technology is increasing. However, due to the nature of the technology itself, it is difficult to determine the scope of the technology to be protected because the scope of the relation is abstract and information disclosure is limited due to the nature of the National Core Technology. To solve this problem, we propose the most appropriate literature type and method of analysis to distinguish important technologies related to National Core Technology. We conducted a pilot test to apply TF-IDF, and LDA topic modeling, two techniques of text mining analysis for big data analysis, to four types of literature (news, papers, reports, patents) collected with National Core Technology keywords in the field of Display industry. As a result, applying LDA theme modeling to patent data are highly relevant to National Core Technology. Important technologies related to the front and rear industries of displays, including OLEDs and microLEDs, were identified, and the results were visualized as networks to clarify the scope of important technologies associated with National Core Technology. Throughout this study, we have clarified the ambiguity of the scope of association of technologies and overcome the limited information disclosure characteristics of national core technologies.

• Knowledge Management Research
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• v.22 no.2
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• pp.145-165
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• 2021

As of late December 2019, the spread of COVID-19 pandemic began which put the entire world in panic. In order to overcome the crisis and minimize any subsequent damage, the government as well as its affiliated institutions must maximize effects of pre-existing policy support and introduce a holistic response plan that can reflect this changing situation- which is why it is crucial to analyze social topics and people's interests. This study investigates people's major thoughts, attitudes and topics surrounding COVID-19 pandemic through the use of social media and big data. In order to collect public opinion, this study segmented time period according to government countermeasures. All data were collected through NAVER blog from 31 December 2019 to 12 December 2020. This research applied TF-IDF keyword extraction and LDA topic modeling as text-mining techniques. As a result, eight major issues related to COVID-19 have been derived, and based on these keywords, this research presented policy strategies. The significance of this study is that it provides a baseline data for Korean government authorities in providing appropriate countermeasures that can satisfy needs of people in the midst of COVID-19 pandemic.

• Journal of Industrial Convergence
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• v.19 no.6
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• pp.11-19
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• 2021

The purpose of this study is to explore trends in research at home and abroad related to "Sport Facilities", and seek the direction of further research. 1,801 abstracts of papers including "Sport Facilities" were collected from the SCOPUS DB from 2016 to 2020. Topic modeling techniques based on Latent Dirichlet Allocation (LDA) algorithm implemented in R language, TD-IDF techniques, and word cluds using Tagxedo was conducted to analyze the data. As a result, 8 topics were optimally determined, and "sports", "facilities", "health", "physical", "data", and "using" were derived as the main keywords for topics. This results indicated that studies on physical activity, health and using facilities regarding sports facilities at home and abroad have been actively carried out in recent years. This indicates that papers in SCOPUS DB are paying attention to the instrumental value of sport facilities, such as health promotion and improving the quality of life. Therefore, various studies that help participants who use sport facilities for a healthy life should be continuously conducted in the future.