• 대한공업교육학회지
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• v.44 no.1
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• pp.141-161
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• 2019

The purpose of this study was to elucidate the necessity of opening a lecture on intellectual property education by confirming the effect of the lecture on intellectual property education in the college students. For the study, IP program was developed for the course through literature review, and supplemented it with expert review. The developed course program was applied to 39 students for 15 weeks. In order to verify the effectiveness of the lecture, the survey was performed. And analysis method for the concept change analysis and the keyword formation analysis were performed. For the analysis, SPSS 24, UCINET and Netdraw were used. The results were as follows. First, the lecture on intellectual property education positively changed the value, necessity, and perception of intellectual property to the students. Second, the students of the lecture on intellectual property education responded that the lecture on the intellectual property should be increased. Third, through the lecture on intellectual property education, students formed basic concept about intellectual property centered on key word. The intellectual property lecture program developed and applied in this study is difficult to apply to all university situations, but it is expected to be referenced in the establishment and operation of related lectures and to be derived in various forms.

• The Journal of Industrial Distribution & Business
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• v.12 no.1
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• pp.47-62
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• 2021

Purpose: Our purpose in this study was to examine the strategies for the development of watermelon industry using unstructured big data analysis. That is, this study was to look the change of issues and consumer's perception about watermelon using big data and social network analysis and to investigate ways to strengthen the competitiveness of watermelon industry based on that. Methodology: For this purpose, the data was collected from Naver (blog, news) and Daum (blog, news) by TEXTOM 4.5 and the analysis period was set from 2015 to 2016 and from 2017-2018 and from 2019-2020 in order to understand change of issues and consumer's perception about watermelon or watermelon industry. For the data analysis, TEXTOM 4.5 was used to conduct key word frequency analysis, word cloud analysis and extraction of metrics data. UCINET 6.0 and NetDraw function of UCINET 6.0 were utilized to find the connection structure of words and to visualize the network relations, and to make a cluster of words. Results: The keywords related to the watermelon extracted such as 'the stalk end of a watermelon', 'E-mart', 'Haman', 'Gochang', and 'Lotte Mart' (news: 015-2016), 'apple watermelon', 'Haman', 'E-mart', 'Gochang', and' Mudeungsan watermelon' (news: 2017-2018), 'E-mart', 'apple watermelon', 'household', 'chobok', and 'donation' (news: 2019-2020), 'watermelon salad', 'taste', 'the heat', 'baby', and 'effect' (blog: 2015-2016), 'taste', 'watermelon juice', 'method', 'watermelon salad', and 'baby' (blog: 2017-2018), 'taste', 'effect', 'watermelon juice', 'method', and 'apple watermelon' (blog: 2019-2020) and the results from frequency and TF-IDF analysis presented. And in CONCOR analysis, appeared as four types, respectively. Conclusions: Based on the results, the authors discussed the strategies and policies for boosting the watermelon industry and limitations of this study and future research directions. The results of this study will help prioritize strategies and policies for boosting the consumption of the watermelon and contribute to improving the competitiveness of watermelon industry in Korea. Also, it is expected that this study will be used as a very important basis for agricultural big data studies to be conducted in the future and this study will offer watermelon producers and policy-makers practical points helpful in crafting tailor-made marketing strategies.

• Journal of the Korean Society of Earth Science Education
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• v.13 no.3
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• pp.226-237
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• 2020

The purpose of the research is to analyze research trends related to climate change education by network analysis based on keywords extracted from the research title. For this purpose, 62 papers were selected from Korean Citation Index(KCI) journals published from 2011 to 2020 using such keywords as "climate change" and "climate change education" in the Research Information Sharing Service. The analysis procedure consisted of selection of analysis papers, keyword extraction and purification, and keyword network analysis and visualization. Textom, Ucinet 6.0, and NetDraw were used to analyze the frequency, degree centrality, and betweenness centrality. The results of the research showed that, first, Early 'Energy and Climate Change Education' had the highest frequency of papers examining climate change education. Second, the keywords/phrases that appeared most frequently in research on climate change education were "program" "energy," "analysis," "elementary school," "elementary school," "elementary school students," "development," and "impact." Third, the analysis of the centrality of betweenness centrality showed that the index of 'program', 'primary students' and 'primary schools' were the highest, and the largest group was 'development and effect of teaching and learning programs'. Based on these results, it was concluded that future research on climate change education needs to be examined in further detail and expanded into more specific areas.

• Journal of the Korean Society for information Management
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• v.38 no.1
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• pp.169-190
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• 2021

Research in various academic fields using network analysis techniques has been conducted and grown. This study performed bibliographical analysis and content analysis on a total of 2,187 network analysis papers published in journals from 2003 to 2021. The results showed that the fields of Pedagogy, Interdisciplinary Research, Computer Science, Library and Information Science, Public Administration, and Business Administration were higher in terms of the number of research papers. From the perspective of journal, mega-journals were indicated as the most productive journals. However, when looking at the impact based on the number of citations, the strength of Public Administration, Library and Information Science, and Pedagogy is clearly revealed. The results of the analysis by authors can also confirm the higher impact of Journalism, Public Administration Science, and Library and Information Science. Of the 1,537 authors identified, very few authors are active in research, confirming the need to expand the researcher base. The results of content analysis showed that the weighted and non-directional network was the most common network type with using the research papers as a data set. Generally nodes are expressed as words and links are expressed as relationship. For network analysis, the use of KrKwic, UCINET, NetMiner, and NetDraw is the most prominent.

• The Journal of the Convergence on Culture Technology
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• v.8 no.2
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• pp.343-348
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• 2022

This study aims to analyze the user experience of unmanned checkout counters perceived by consumers using SNS big data. For this study, blogs, news, intellectuals, cafes, intellectuals (tips), and web documents were analyzed on Naver and Daum, and 'unmanned checkpoints' were used as keywords for data search. The data analysis period was selected as two years from January 1, 2020 to December 31, 2021. For data collection and analysis, frequency and matrix data were extracted through Textom, and network analysis and visualization analysis were conducted using the NetDraw function of the UCINET 6 program. As a result, the perception of the checkout counter was clustered into accessibility, usability, continuous use intention, and others according to the definition of consumers' experience factors. From a supplier's point of view, if unmanned checkpoints spread indiscriminately to solve the problem of raising the minimum wage and shortening working hours, a bigger employment problem will arise from a social point of view. In addition, institutionalization is needed to supply easy and convenient unmanned checkout counters for the elderly and younger generations, children, and foreigners who are not familiar with unmanned calculation.

• Journal of the Korea Society of Computer and Information
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• v.27 no.7
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• pp.115-124
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• 2022

The purpose of this study is to analyze and present keywords, trends, and language networks of keywords for each year of the pedagogical exam of the secondary teacher's employment exam for the 2019~2022 school year. The main research methods were text mining technique and language network analysis method, and analysis programs were KrKwic, Wordcloud Maker, Ucinet6, NetDraw, etc. The research results are as follows; First, keywords such as teacher, student, curriculum, class, and evaluation appeared in the top rankings, and keywords (online, wiki, discussion ceremony, information, etc.) that reflect the recent online class progress in the current COVID-19 situation also tended to appear. The keywords with high frequency of occurrence in the four-year integrated text were student(44), teacher(39), class(27), school(18), curriculum(16), online(10), and discussion method(8). Second, the overall language network of the keywords with high frequency of 4 years showed a significant level of density(0.566), total number of links(492), and average degree of links(16.4). The degree centrality was found in the order of teacher(199.0), class(197.0), student(185.0), and school(150.0). Betweenness centrality was found in the order of teacher(30.859), class(18.956), student(16.054), and school (15.745). It is expected that the results of this study will serve as data to be considered for preparatory teachers, institutions and related persons, and teachers and administrators of secondary school teacher training institutions.

• Journal of the Korea Convergence Society
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• v.13 no.5
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• pp.313-325
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• 2022

The purpose of this study is to examine the changes in the elderly healthcare app market through text mining analysis and to present basic data for activating elderly healthcare apps. Data collection was conducted on Naver, Daum, blog web, and cafe. As for the research method, text mining, TF-IDF(Term frequency-inverse document frequency), emotional analysis, and semantic network analysis were conducted using Textom and Ucinet6, which are big data analysis programs. As a result of this study, a total of six categories were finally derived: resolving the healthcare app information gap, convergence healthcare technology, diffusion media, elderly healthcare app industry, social background, and content. In conclusion, in order for elderly healthcare apps to be accepted and utilized by the elderly, they must have a good diffusion infrastructure, and the effectiveness of healthcare apps must be maximized through the active introduction of convergence technology and content development that can be easily used by the elderly.

• Journal of Korean Home Economics Education Association
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• v.34 no.2
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• pp.1-19
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• 2022

The purpose of this study is to analyze the keywords of the middle school textbooks based on the 2015 revision of the technology and home economics curriculum to understand the core concepts and contents composition of the 'housing' unit. Using TEXTOM and UCINET programs, the frequencies and centralities of the keywords were analyzed, and CONCOR analysis was performed. The results are as follows. First, the content system of the 'housing' unit is divided into 'life culture' and 'safety' in the 'family life and safety' area. Second, in the 'safety' section, the frequencies of occurrence of the words were high in the order of indoor, occurrence, use, noise, and safety accidents, in the order of frequency of occurrence. It was confirmed that words related to daily life, safety accidents, and prevention were closely connected to each other. In the 'life culture' section, the frequencies of occurrence were high in the order of space, housing, family, and residential space, and the correlations between these keywords were also high. Third, the most influential core keywords were, indoor and occurrence in the 'safety' section, and space, family, and housing, in the 'life culture' section. Fourth, the 'safety' section were divided into two subunits, 'safe living environment' and 'comfortable living environment', and the 'life culture' section were divided into four subunits, 'living space composition', 'space utilization', 'housing value and lifestyle', and 'housing culture'.

• Journal of Internet Computing and Services
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• v.24 no.1
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• pp.71-86
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• 2023

The purpose of this exploratory study is to compare the differences in public perceptual characteristics of Korean and Chinese societies regarding the metaverse using big data analysis. Due to the environmental impact of the COVID-19 pandemic, technological progress, and the expansion of new consumer bases such as generation Z and Alpha, the world's interest in the metaverse is drawing attention, and related academic studies have been also in full swing from 2021. In particular, Korea and China have emerged as major leading countries in the metaverse industry. It is a timely research question to discover the difference in social awareness using big data accumulated in both countries at a time when the amount of mentions on the metaverse has skyrocketed. The analysis technique identifies the importance of key words by analyzing word frequency, N-gram, and TF-IDF of clean data through text mining analysis, and analyzes the density and centrality of semantic networks to determine the strength of connection between words and their semantic relevance. Python 3.9 Anaconda data science platform 3 and Textom 6 versions were used, and UCINET 6.759 analysis and visualization were performed for semantic network analysis and structural CONCOR analysis. As a result, four blocks, each of which are similar word groups, were driven. These blocks represent different perspectives that reflect the types of social perceptions of the metaverse in both countries. Studies on the metaverse are increasing, but studies on comparative research approaches between countries from a cross-cultural aspect have not yet been conducted. At this point, as a preceding study, this study will be able to provide theoretical grounds and meaningful insights to future studies.

• Journal of the Korea Convergence Society
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• v.13 no.1
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• pp.71-80
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• 2022

The purpose of this study is to analyze the social perception of invention education center using big data analysis method. For this purpose, data from January 2014 to September 2021 were collected using the Textom website as a keyword searched for 'invention+education+center' in blogs, cafes, and news channels of NAVER and DAUM website. The collected data was refined using the Textom website, and text mining analysis and semantic network analysis were performed by the Textom website, Ucinet 6, and Netdraw programs. The collected data were subjected to a primary and secondary refinement process and 60 keywords were selected based on the word frequency. The selected key words were converted into matrix data and analyzed by semantic network analysis. As a result of text mining analysis, it was confirmed that 'student', 'operation', 'Korea Invention Promotion Association', and 'Korean Intellectual Property Office' were the meaningful keywords. As a result of semantic network analysis, five clusters could be identified: 'educational operation', 'invention contest', 'education process and progress', 'recruitment and support for business', and 'supervision and selection institution'. Through this study, it was possible to confirm various meaningful social perceptions of the general public in relation to invention education center on the internet. The results of this study will be used as basic data that provides meaningful implications for researchers and policy makers studying for invention education.