• Journal of the Korean Society of Marine Environment & Safety
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• v.30 no.1
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• pp.32-42
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• 2024

In this study, 1,474 effective patents were derived for quantitative analysis of five major countries, including Korea, China, Japan, the United States and Europe, for marine space policy simulator technology used as a support for integrated marine space management means, and domestic technology competitiveness and domestic and foreign technology trends were identified through annual and national patent application trends and word cloud analysis. This diagnosed the need for active policy support for research and development of marine space policy simulator technology at the government level and preparation through linkage strategies such as patent application consideration and standardization preoccupation for surrounding technologies to prepare for China-led market monopoly and preoccupation.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.374-390
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• 2021

Growth and yield of field vegetable crops would be affected by climate conditions, which cause a relatively large fluctuation in crop production and consumer price over years. The yield prediction system for these crops would support decision-making on policies to manage supply and demands. The objectives of this study were to compile literatures related to onion and garlic and to perform data-mining analysis, which would shed lights on the development of crop models for these major field vegetable crops in Korea. The literatures on crop growth and yield were collected from the databases operated by Research Information Sharing Service, National Science & Technology Information Service and SCOPUS. The keywords were chosen to retrieve research outcomes related to crop growth and yield of onion and garlic. These literatures were analyzed using text mining approaches including word cloud and semantic networks. It was found that the number of publications was considerably less for the field vegetable crops compared with rice. Still, specific patterns between previous research outcomes were identified using the text mining methods. For example, climate change and remote sensing were major topics of interest for growth and yield of onion and garlic. The impact of temperature and irrigation on crop growth was also assessed in the previous studies. It was also found that yield of onion and garlic would be affected by both environment and crop management conditions including sowing time, variety, seed treatment method, irrigation interval, fertilization amount and fertilizer composition. For meteorological conditions, temperature, precipitation, solar radiation and humidity were found to be the major factors in the literatures. These indicate that crop models need to take into account both environmental and crop management practices for reliable prediction of crop yield.

• Journal of Practical Agriculture & Fisheries Research
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• v.22 no.1
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• pp.113-129
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• 2020

In this study we examined the topic analysis and correlation analysis by text mining to extract meaningful information or rules from the self introduction letter of freshman at Korea National College of Agriculture and Fisheries in 2020. The analysis items are described in items related to 'academic' and 'in-school activities' during high school. In the text mining results, the keywords of 'academic' items were 'study', 'thought', 'effort', 'problem', 'friend', and the key words of 'in-school activities' were 'activity', 'thought', 'friend', 'club', 'school' in order. As a result of the correlation analysis, the key words of 'thinking', 'studying', 'effort', and 'time' played a central role in the 'academic' item. And the key words of 'in-school activities' were 'thought', 'activity', 'school', 'time', and 'friend'. 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. In the next study, TF-IDF(Term Frequency-Inverse Document Frequency) analysis using 'frequency of keywords' and 'reverse of document frequency' will be performed as a method of extracting key words from a large amount of documents.

• 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 Korean Home Economics Education Association
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• v.27 no.4
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• pp.37-50
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• 2015

The purpose of this study was to analyze the core content of consumer area from 1st to 2009 revised middle school Home Economics textbooks with the aim of proposing guidelines. An in-depth content analysis was conducted twenty two Home Economics textbooks that have been used in middle schools, beginning with the first curriculum until the revised 2009 curriculum with word cloud. The major findings of this study were as follows; First, the first period of the textbooks emphasized thrift-related concepts such as budgeting and saving money. The second and third period in Home Economics textbooks focused on household work and resource management. From fifth period, the content of textbooks were emphasized learning how to find relevant information and making rational decisions as a consumer. The 2007 revised and 2009 revised period in Home Economics have focused on rational decision-making by adolescents, while taking into account environmental considerations. The content of textbooks now introduces students to the notions of ethical consumerism and eco-friendly consumption across domains such as clothing, food, and housing. The curriculum and content of textbooks in Home Economics should emphasize the concepts related to ethical consumption.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.7
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• pp.371-378
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• 2017

Recently, with the spread of smart device and the introduction of web services, the data is rapidly increasing online, and it is utilized in various fields. In particular, the emergence of social media in the big data field has led to a rapid increase in the amount of unstructured data. In order to extract meaningful information from such unstructured data, interest in big data technology has increased in various fields. Big data is becoming a key resource in many areas. Big data's prospects for the future are positive, but concerns about data breaches and privacy are constantly being addressed. On this subject of big data, where positive and negative views coexist, the research of analyzing people's opinions currently lack. In this study, we compared the changes in peoples perception on big data based on unstructured data collected from the social media using a text mining. As a results, yearly keywords for domestic big data, declining positive opinions, and increasing negative opinions were observed. Based on these results, we could predict the flow of domestic big data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.46-53
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• 2020

The purpose of this study was to examine the direction of social welfare education in the 4th Industrial Revolution as well as discuss the overall direction of social welfare education such as competency and curriculum and the educational dimension of social welfare professionals. Using Text Network Analysis, 223 studies published from 2005 to 2019 in the Korean Journal of Social Welfare Education were examined in order to explore the direction of social welfare education in the 4th Industrial Revolution. Using Word cloud, overall frequency was analyzed. As a result of key words analysis, social welfare education (43), research method (28), and social welfare field practice (23) were analyzed as influential key words. The directions of social welfare education in the 4th Industrial Revolution era are as follows. First, competency, curriculum, and qualifications are necessary in general social welfare education. Second, education centering on social workers and social welfare students, who are social welfare professionals, is necessary. Third, the ethical sensitivity of future social welfare should be carefully established. Finally, the need for a shared welfare system must be further studied.

• The Journal of the Korea Contents Association
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• v.20 no.9
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• pp.208-223
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• 2020

In the 21st general election held in April 15, 2020, the importance of social media as an election campaigning tool became more prominent when engaged with Corona 19. Therefore, in this study, various studies were conducted to establish SNS strategy as an election campaign tool. This study analyzed the contents of SNS (Facebook, Twitter, YouTube) activities as an election campaign tool to analyze messages on social media messages of candidates Lee Nak-yeon and candidate Hwang Kyo-an of Jongno-gu, Seoul during the 2020 21st National Assembly election. Data collection mainly analyzed posts from each candidate's official account, and the research method used text analysis using the R program. Word cloud, comparative analysis, q-graph analysis, LDA, and STM analysis were used during text analysis. In addition, the analysis result was confirmed to be statistically significant through correlation analysis. As a result of research, candidate Lee Nak-yeon's election includes corona, people, problems, crisis, suffering, and wisdom, which indicates that the crisis caused by corona must be overcome through any means possible. On the other hand, candidate Hwang Kyo-an's election includes Moon Jae-in, the regime, save, the fatherland, the judge, and the economy. And from the perspective of political publicity, candidate Lee Nak-yeon made a lot of acclaims, while candidate Hwang Kyo-an made a lot of attacks, and both themes emphasized the policy rather than the image.

• Journal of Korean Home Economics Education Association
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• v.32 no.3
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• pp.179-197
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• 2020

This study analyzed the trends in home economics education research using the language network analysis method, focusing on papers published in the KCI list for 20 years from 2000 to 2019. A total of 501 home economics education papers analyzed through word cloud, centrality analysis, and topic modeling using NetMiner 4.4, and the results are as follows. First, the number of papers in home economics education published in the KCI listing increased gradually to 186 in the 2000s and 315 in the 2010s. The academic journals in which home economics education papers were published have been diversified to 16 in the 2000s and 22 in the 2010s. 60% of all papers were published in the 'Journal of Korean Home Economics Education Association', and since 2018, the number of papers published in the 'Journal of Learner-Centered Curriculum and Instruction' has increased dramatically. Second, in the 2000s and 2010s, home economics education studies published in KCI were categorized into home economics education content analysis, home economics educational program development & application, curriculum analysis, perception survey & direction exploration. In the 2000s, 'Home Economics Teacher' appeared as the main keyword, and a lot of perception survey & direction exploration were conducted. Relatively, the influence of 'development' increased in the 2010s, and many studies were conducted to analyze home economics education contents and develop and apply home economics programs. This study has significance in that it analyzed the research trend of HEE by expanding the analysis target and analysis period of the existing studies.

• The Korean Journal of Applied Statistics
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• v.30 no.4
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• pp.603-613
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• 2017

Many people have recently posted about personal interests on social media. The development of the Internet and computer technology has enabled the storage of digital forms of documents that has resulted in an explosion of the amount of textual data generated; subsequently there is an increased demand for technology to create valuable information from a large number of documents. A text mining technique is often used since text-based data is mostly composed of unstructured forms that are not suitable for the application of statistical analysis or data mining techniques. This study analyzed the Meteorological Yearbook data of the Korea Meteorological Administration (KMA) with a text mining technique. First, a term dictionary was constructed through preprocessing and a term-document matrix was generated. This term dictionary was then used to calculate the annual frequency of term, and observe the change in relative frequency for frequently appearing words. We also used regression analysis to identify terms with increasing and decreasing trends. We analyzed the trends in the Meteorological Yearbook of the KMA and analyzed trends of weather related news, weather status, and status of work trends that the KMA focused on. This study is to provide useful information that can help analyze and improve the meteorological services and reflect meteorological policy.