• Journal of Korean Society of Forest Science
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• v.110 no.3
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• pp.308-321
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• 2021

The purpose of this study was to analyze domestic research trends over the past 20 years and future direction of forest ecology using text mining. A total of 1,015 academic papers and keywords data related to forest ecology were collected by the "Research and Information Service Section" and analyzed using big data analysis programs, such as Textom and UCINET. From the results of word frequency and N-gram analyses, we found domestic studies on forest ecology rapidly increased since 2011. The most common research topic was "species diversity" over the past 20 years and "climate change" became a major topic since 2011. Based on CONCOR analysis, study subjects were grouped intoeight categories, such as "species diversity," "environmental policy," "climate change," "management," "plant taxonomy," "habitat suitability index," "vascular plants," and "recreation and welfare." Consequently, species diversity and climate change will remain important topics in the future and diversifying and expanding domestic research topics following global research trendsis necessary.

• Journal of the Society of Disaster Information
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• v.20 no.2
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• pp.462-469
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• 2024

Purpose: This study aims to analyze data on disaster safety education for migrant youth and to examine the corresponding social perceptions. Method: Data on disaster safety education for migrant youth were collected and analyzed using Textom and Ucinet. The data used in the study were searched on portal websites from 2016 to 2023 using the keywords 'migrant youth+ disaster + safety education'. Result: The analysis results showed that 'education (306)' had the highest frequency, followed by 'safety (287)', 'school (97)', 'society (85)', and 'support (77)'. The keyword with the high degree of centrality, closeness centrality, and betweenness centrality were 'education', 'safety' and 'society'. 'Family' ranked higher in betweenness centrality than the rankings of frequency analysis, degree centrality and closeness centrality, indicating that 'family' plays a significant role as a mediator in the network of disaster safety education for migrant youth. Conclusion: By examining social awareness about disaster safety education for migrant youth, the findings will be used to develop policies and strategies for disaster safety education that consider the unique vulnerabilities of migrant youth in disaster situations.

• Journal of the Korea Convergence Society
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• v.11 no.6
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• pp.145-151
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• 2020

'Hansik', or Korean cuisine is one of Korea national brands. To understand the domestic consumer awareness of Korean cuisine, data was gathered under the keyword search, 'Hansik.' Textom 3.5 was used to gather data from blogs, news media found on Naver from November 1, 2018, to October 31, 2019. The results from frequency and TF-IDF analysis indicate that the 'buffet' had the largest proportion in terms of consumer awareness to Hansik. Also, broadcasting contents starring star chefs had a great influence. The Hansik awareness did not remain in the domains of its traditionality, but also branched into extents into areas such as fusional and gourmet cuisine. UCINET6 and NetDraw were used to conduct CONCOR analysis. Four cluster formations have been found; various food cultural cluster, high-end restaurant cluster referring to aired restaurants on media, Hansik brand cluster, and Hansik buffet cluster. This study proposes presenting a various menu of Hansik which use a multiple number of ingredients. Also, a promotion that introduces fine Hansik and a development of marketing views and media contents about the convenient HMRs make the associated imagery of Hansik to be strengthen.

• 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 Korean Society of Forest Science
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• v.111 no.1
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• pp.36-49
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• 2022

The purpose of this study was to analyze domestic research trends related to the Baekdudaegan Mountains in the last two decades. In total, 551 academic papers and keyword data related to the Baekdudaegan Mountains were collected using the "Research and Information Service Section" and analyzed using "big data" analysis programs, such as Textom and UCINET. Papers related to the Baekdudaegan Mountains were published in 177 academic journals, and 229 papers (41.6% of all published papers) were published between 2011 and 2015. According to word frequency data (N-gram analyses), the major research topic over the past 20 years was "species diversity." According to CONCOR analysis results, the main research could be divided into 15 areas, the most important of which was "species diversity," followed by "vegetation restoration and management," and "culture." Ecological research comprised 12 groups with a frequency of 78.8%; humanities and social research comprised 2 groups with a frequency of 15.6%. Overall, our study of research areas and quantitative data analyses provides valuable information that could help establish policy formulation.

• The Mathematical Education
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• v.52 no.4
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• pp.483-496
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• 2013

In this study, we investigated the structure of the mathematics education scholars' co-authorship relationship in papers registered at the National Research Foundation of Korea by social network analysis. The data were 354 scholars from 257 papers in 4 journals from 2009 to 2013 based on 'the 2009 revised Korean National Curriculum'. For the analysis, Pajek3 and UCINET6.3 were used. The results of this study were as follows: First, each of the mathematics education scholars is connected on average with about 5 paths of intermediate collaborators. Second, Analyses of the first component group found distinguishable scholar groups' characteristics depending on their affiliations, majors, and job statuses. Third, there were scholars having high values in network degree centrality measures despite not having high numbers in published papers. On the contrary, there sere scholars having high numbers in published papers despite not having high values in network analysis. Finally, I suggested the directions for the future research with the limitations of this study.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.23 no.1
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• pp.14-23
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• 2015

This study applied the network text analysis to reveal the scope and trends of low cost carrier studies. We analyzed low cost carrier research published in Korean journals and news articles. The results showed that there are three clusters in terms of research topics. First dimension consists of articles investigating growth in the low cost carrier industry. The second dimension is associated with service characteristics. The last dimension has strong ties organizational and human resource dimension. We run Krkwic, Krtitle, Netdraw, and Ucinet 6.0 to conduct the network text analysis. This study suggests the direction of low cost carrier research in the future.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.197-200
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• 2018

The aim of current research is to suggest a interface for movie reviews at a glance through semantic network analysis. The implication of this study is to systematically investigate the structure of eWoM. Specifically, by visualizing semantic networks of movie reviews this study attempts to provide a prototype of a possible review system that can check the response of movie viewer at a glance.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.2
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• pp.133-141
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• 2018

The purpose of this study was to propose a model of knowledge transfer in IT outsourcing. In this study, structural holes were chosen as antecedent factors, and job performance as a consequence factor. We conducted a survey in which we collected data from 42 respondents working in one of the leading IT companies in Seoul, South Korea. The data were analyzed using UCINET 6 and SmartPLS 2.0. The antecedent factors (structural holes in closeness network and in professional network) turned out to be statistically significant. Knowledge transfer considerably influenced job performance. Lastly, implications and limitations of these findings were discussed, and directions for future research were suggested.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.98-108
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• 2022

In this study, social network analysis was performed to compare and analyze changes in domestic tourism trends before and after the outbreak of COVID-19 in a situation where the damage to the tourism industry due to COVID-19 is increasing. Using Textom, a big data analysis service, data were collected using the keywords "travel destination" and "travel trend" based on the collection period of 2019 and 2020, when the epidemic spread to the world and became chaotic. After extracting a total of 80 key words through text mining, centrality was analyzed using NetDraw of Ucinet6, and clustered into 4 groups through CONCOR analysis. Through this, we compared and analyzed changes in domestic tourism trends before and after the outbreak of COVID-19, and it is judged to provide basic data for tourism marketing strategies and tourism product development in the post-COVID-19.