• The Journal of Engineering Geology
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• v.31 no.3
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• pp.307-319
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• 2021

Although it is currently conducting slope management and research using digital technologies such as drones, big data, and artificial intelligence, it is still somewhat insufficient and is still vulnerable to slope failure. For this reason, it is inevitable to present the development direction for research on prediction and analysis of slope failure using the digital technologies to effectively deal with slope failure, which requires a preemptive understanding of prediction and analysis of slope failure. In this paper, we collected literature data based on the Web of Science for five years from January 1, 2016 to December 31, 2020 and analyzed by co-word analysis to identify the domain structure of research on prediction and analysis of slope failure. Detailed subject areas were identified through network analysis, and the domain relationships between keywords were visualized to derive global and regionally oriented keywords through relationship, centrality analysis. In addition, the clusters formed by performing cluster analysis were displayed on the multidimensional scailing map, and the domain structure according to the correlation between each keyword was presented. The results of this study reveal the domain structure of research on prediction and analysis of slope failure, and are expected to be usefully used to find future research directions.

• Journal of Environmental Impact Assessment
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• v.31 no.5
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• pp.310-320
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• 2022

This study aimed to identify the change in the public perception of "bats" after the outbreak of the coronavirus (COVID-19) infection. Text mining and network analysis were conducted for blog posts, the largest social network in Korea. We collected 9,241 Naver blog posts from 2019 to 2020 just before the outbreak of COVID-19 in Korea. The data were analyzed with Python and NetMiner 4.3.2, and the public's perception of bats was examined through the relationship of keywords by period. Findings indicated that the frequency of bat keywords in 2020 increased more than 25 times compared to 2019, and the centrality value increased more than three times. The perception of bats changed before and after the outbreak of the pandemic. Prior to COVID-19, bats were highly recognized as a species of wildlife while in the first half of 2020, they were strongly considered as a threat to human society in relation to infectious diseases and health. In the second half of 2020, it was confirmed that the area of interest in bats expanded as the proportion of ecological and cultural types ofresearch increased. This study seeks to contribute to the expansion and direction of future research in bats by understanding the public's interest in the potential impact of the species as disease hosts post the COVID-19 pandemic.

• Journal of Korean Society of Rural Planning
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• v.27 no.4
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• pp.13-24
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• 2021

This study used big data to analyze visitors' experiences in Fishing Experience Recreation Village. Through the portal site posting data for the past six years, the experience of visiting Fishing Experience Villages in Baekmi and Susan was analyzed. The analysis method used Text mining and Social Network Analysis which are Big data analysis techniques. Data was collected using Textom, and experience keywords were extracted by analyzing the frequency and importance of experience texts. Afterwards, the characteristics of the experience of visiting the Fishing Experience Village were identified through the analysis of the interaction between the experience keywords using 'U cinet 6.0' and 'NetDraw'. First, through TF and TF-IDF values, keywords such as "Gungpyeong Port", "Susan Port", and "Yacht Marina" that refer to the name of the port and the port facilities appeared at the top. This is interpreted as the name of the port has the greatest impact on the recognition of the Fishing Experience Villages, and visitors showed a lot of interest in the port facilities. Second, focusing on the unique elements of port facilities and fishing villages such as "mud flat experience", "fishing village experience", "Gungpyeong port", "Susan port", "yacht marina", and "beach" through the values of degree, closeness, and betweenness centrality interpreted as having an interaction with various experiences. Third, through the CONCOR analysis, it was confirmed that the visitor's experience was focused on the dynamic behavior, the experience program had the greatest influence on the experience of the visitor, and that the experience of the static and the dynamic behavior was relatively balanced. In conclusion, the experience of visitors in the Fishing Experience Villages is most affected by the environment of the fishing village such as the tidal flats and the coast and the fishing village experience program conducted at the fishing port facilities. In particular, it was found that fishing port facilities such as ports and marinas had a high influence on the awareness of the Fishing Experience Villages. Therefore, it is important to actively utilize the scenery and environment unique to fishing villages in order to revitalize the Fishing Experience Villages experience and improve the quality of the visitor experience. This study is significant in that it studied visitors' experiences in fishing village recreation villages using big data and derived the connection between fishing village and fishing village infrastructure in fishing village experience tourism.

• 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 Elementary Science Education
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• v.42 no.1
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• pp.178-193
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• 2023

The aim of this study was to investigate differences in the achievement standards from the 2015 to the 2022 revised national science curriculum and to present the implications for science teaching under the revised curriculum. Achievement standards relevant to primary science education were therefore extracted from the national curriculum documents; conceptual domains in the two curricula were analyzed for differences; various kinds of centrality were computed; and the Louvain algorithm was used to identify clusters. These methods revealed that, in the revised compared with the preceding curriculum, the total number of nodes and links had increased, while the number of achievement standards had decreased by 10 percent. In the revised curriculum, keywords relevant to procedural skills and behavior received more emphasis and were connected to collaborative learning and digital literacy. Observation, survey, and explanation remained important, but varied in application across the fields of science. Clustering revealed that the number of categories in each field of science remained mostly unchanged in the revised compared with the previous curriculum, but that each category highlighted different skills or behaviors. Based on those findings, some implications for science instruction in the classroom are discussed.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.167-181
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• 2023

This study utilized TEXTOM, a social network analysis program to analyze changes in current tourism behavior after travel restrictions were eased after the outbreak of COVID-19. Data on the keywords 'domestic travel' and 'overseas travel' were collected from blogs, cafes, and news provided by Naver, Google, and Daum. The collection period was set from April to December 2022 when social distancing was lifted, and 2019 and 2020 were each set as one year and compared and analyzed with 2022. A total of 80 key words were extracted through text mining and centrality analysis was performed using NetDraw. Finally, through the CONCOR, the correlated keywords were clustered into 4. As a result of the study, tourism behavior in 2022 shows tourism recovery before the outbreak of COVID-19, segmentation of travel based on each person's preferred theme, prioritization of each country's corona mitigation policy, and then selecting a tourist destination. It is expected to provide basic data for the development of tourism marketing strategies and tourism products for the newly emerging tourism ecosystem after COVID-19.

• Journal of Korean Society of Archives and Records Management
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• v.24 no.2
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• pp.41-63
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• 2024

This study investigated research trends in digital curation indexed in a prominent domestic academic information database. A systematic literature review was conducted on 39 academic papers published from 2009 to 2023. The review examined indexing status according to publication year, venue, academic discipline, research area distribution, research affiliation and occupation, and research types. In addition, network centrality analysis and cohesive group analysis were performed on 69 author keywords. The findings revealed several key points. First, digital curation research peaked in 2015 and 2016 with 5 publications each year, followed by a slight decrease, and then consistently produced 4 or more publications annually since 2019. Second, among the 39 studies, 25 were conducted in interdisciplinary fields, including library and information science, while 11 were in the humanities, such as miscellaneous humanities. The most prominent research areas were theoretical and infrastructural aspects, information management and services, and institutional domains. Third, digital curation research was predominantly led by university-affiliated professors and researchers, with collaborative research more prevalent than solo research. Lastly, analysis of author keywords revealed that "digital curation," "institution," and "content" were the most influential central keywords within the overall network.

• Journal of Korean Dental Hygiene Science
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• v.6 no.2
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• pp.101-114
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• 2023

Background: This study aimed to explore the overall perception of pit and fissure sealants and suggest methods to revitalize their current stagnation. Methods: To determine the social perception of the change in coverage policy for pit and fissure sealants, we categorized them into five time periods. The first period (December 1, 2009 to November 30, 2010), the second period (December 1, 2010 to September 30, 2012), the third period (October 1, 2012 to May 5, 2013), the fourth period (May 6, 2013 to September 30, 2017), and the fifth period (October 1, 2017 to December 31, 2022). We utilized text mining, an unstructured big data analysis method. Keywords were collected and analyzed using Textom, and the frequency analysis of the top 30 keywords, structural features of the semantic network, centrality analysis, QAP correlation analysis, and co-occurrence analysis were conducted. Results: The frequency analysis showed that the top keywords for each time period were 'Cavities', 'Treatment', and 'Children'. In the structural features of the semantic network of pit and fissure sealants by time period, the density index was found to be around 1.00 for all time periods. The QAP correlation analysis showed the highest correlation between the first and second periods and the fourth and fifth periods with a correlation coefficient of 0.834. The co-occurrence analysis showed that 'cavities' and 'prevention were the top two words across all time periods. Conclusion: This study showed that pit and fissure sealants are well accepted by the society as a preventive treatment for caries. However, the awareness of health education related to these sealants was found to be low. Efforts to revitalize stagnant pit and fissure sealants need to be strengthened with effective education.

• Journal of the Economic Geographical Society of Korea
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• v.27 no.3
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• pp.174-191
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• 2024

This study analyzed the spatiotemporal evolution of Korean multinational corporations' (MNCs') foreign direct investment (FDI) networks from 1978 to 2023, focusing on Samsung Electronics and LG Electronics. Using data on the consolidated overseas subsidiaries of these two companies, a two-mode network was constructed to examine the status of host countries through the betweenness centrality index and to identify types of countries with similar value chain arrangements by investigating their linkage structures. The main findings are as follows. First, during the early phase of Korean electronics MNCs' overseas expansion in the 1980s, they primarily established sales bases in developed consumer markets. However, over time, they gradually expanded into other business areas, including manufacturing, producer services, and R&D, increasing complexity in their FDI networks as cross-border mergers and acquisitions (M&As) became more frequent. Second, the United States has remained central to these MNCs' FDI networks since the 1980s, but more recently, China has emerged as a significant hub, challenging the U.S. in global value chains. Third, emerging Asian economies, including India, Vietnam, and Indonesia, have strengthened their positions due to the diversification of MNCs' investment objectives from manufacturing bases to a broader range of business areas. Finally, since the 2010s, the convergence of the electronics industry with the automotive electronics sector and new industries has led to a diversification of the value chain arrangements of Korean electronics MNCs.

• Journal of Life Science
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• v.30 no.1
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• pp.45-57
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• 2020

The prenatal period in livestock animals is crucial for meat production because net increase in the number of muscle fibers is finished before birth. However, there is no study on the growth and development mechanism of muscles in Hanwoo during this period. Therefore, to find candidate genes involved in muscle growth and development during this period in Hanwoo, mRNA expression data of longissimus in Hanwoo at 6 and 9 months post-conceptional age (MPA) were analyzed. We independently identified differentially expressed genes (DEGs) using DESeq2 and edgeR which are R software packages, and considered the overlaps of the results as final-DEGs to use in downstream analysis. The DEGs were classified into several modules using WGCNA then the modules' functions were analyzed to identify modules which involved in myogenesis and adipogenesis. Finally, the hub genes which had the highest WGCNA module membership among the top 10% genes of the STRING network maximal clique centrality were identified. 913(6 MPA specific DEGs) and 233(9 MPA specific DEGs) DEGs were figured out, and these were classified into five and two modules, respectively. Two of the identified modules'(one was in 6, and another was in 9 MPA specific modules) functions was found to be related to myogenesis and adipogenesis. One of the hub genes belonging to the 6 MPA specific module was axin1 (AXIN1) which is known as an inhibitor of Wnt signaling pathway, another was succinate-CoA ligase ADP-forming beta subunit (SUCLA2) which is known as a crucial component of citrate cycle.