• Ecology and Resilient Infrastructure
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• v.7 no.3
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• pp.189-198
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• 2020

Wetlands, which provide various ecological services, have been regarded as an important nature-based solution for, for example, sustainable water quality improvement and buffering of impacts from climate change. Although the importance of conserving wetlands to reduce the impacts of various perturbations (e.g., changes of land use, climate, and hydrology) has been acknowledged, the possibility of applying these efforts as a nature-based solution in a macro-scale (e.g., landscape) has been insufficient. In this study, we examine the possibility of ecological network analysis that provides an engineering solution as a nature-based solution. Specifically, we analyzed how land use change affects the structural and functional characteristics (connectivity, network efficiency, and clustering coefficient) of the ecological networks by using the ecological networks generated by multiple dispersal models of the hypothetical inhabiting species in wetlandscape. Changes in ecological network characteristics were analyzed through simultaneously removing wetlands, with two initial conditions for surface area, in the zones where land use change occurs. We set a total number of four zones of land use change with different wetland densities. All analyses showed that mean degree and network efficiency were significantly reduced when wetlands in the zones with high wetland density were removed, and this phenomenon was intensified especially when zones contained hubs (nodes with high degree). On the other hand, we observed the clustering coefficient to increase. We suggest our approach for assessing the impacts of land use change on ecological networks, and with additional analysis on betweenness centrality, we expect it can provide a nature-based engineering solution for creating alternative wetlands.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.1
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• pp.39-48
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• 2016

The tacit knowledge transfer cultivate the value and mount of tacit knowledge. The tacit knowledge transfer plays the most important role for improving the competitiveness of the organization. Despite the tacit knowledge transfer is very important, the research related with tacit knowledge transfer has not been actively carried out. The barriers to tacit knowledge transfer interfere with the tacit knowledge transfer. The barriers to tacit knowledge transfer are lack of understanding knowledge experts, heavy over-work, insufficient compensation, trust shortage and knowledge stickiness. In order to overcome the barrier of the tacit knowledge transfer, it is necessary to promote knowledge broker. The knowledge broker is the foundation for the tacit knowledge transfer and the critical success factor for efficient tacit knowledge transfer. However, most research related on the knowledge broker had focused on the degree, centrality and density of the knowledge network. The framework is needed to performance indicator for diagnosing the tacit knowledge transfer. Therefore, we suggest the knowledge broker framework based on the social network analysis.

• Journal of Industrial Convergence
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• v.21 no.1
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• pp.187-192
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• 2023

In this study, trends in ICT education were investigated by analyzing the frequency of appearance of keywords related to machine learning and using conversion of iteration correction(CONCOR) techniques. A total of 304 papers from 2018 to the present published in registered sites were searched on Google Scalar using "ICT education" as the keyword, and 60 papers pertaining to ICT education were selected based on a systematic literature review. Subsequently, keywords were extracted based on the title and summary of the paper. For word frequency and indicator data, 49 keywords with high appearance frequency were extracted by analyzing frequency, via the term frequency-inverse document frequency technique in natural language processing, and words with simultaneous appearance frequency. The relationship degree was verified by analyzing the connection structure and centrality of the connection degree between words, and a cluster composed of words with similarity was derived via CONCOR analysis. First, "education," "research," "result," "utilization," and "analysis" were analyzed as main keywords. Second, by analyzing an N-GRAM network graph with "education" as the keyword, "curriculum" and "utilization" were shown to exhibit the highest correlation level. Third, by conducting a cluster analysis with "education" as the keyword, five groups were formed: "curriculum," "programming," "student," "improvement," and "information." These results indicate that practical research necessary for ICT education can be conducted by analyzing ICT education trends and identifying trends.

• The Journal of Society for e-Business Studies
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• v.21 no.3
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• pp.79-99
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• 2016

Supply network of automobile part is addressed with the e-invoices generated at real time. Automobile is composed of 8 modules. Firms which produce these modules are defined as the first outsourcing firm. Brake is the part of power control module and so, brake manufacturing firm is called the second outsourcing firm. In this paper, the third supply networks of brake manufacturing firms is analyzed with e-invoices and social network method. At the node-level, the third outsourcing firms are classified into 3 categories, interator, allocator and hub with respect to their role at the ego-network of each brake manufacturing firm. At the network level, A2, one of 3 brake manufacturing firms have more outsourcing firms and bigger centrality than the other brake manufacturing firms. Intre-firms trade patterns are, also, analyzed by using the degree of trade dedication with respect to the modes of business. It is shown that trade pattern of retail, commodity brokerage firm, rubber and plastic manufacturing firm are hierarchical trade because their degree of trade dedication is almost near to 1.

• 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 Korean Society of Rural Planning
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• v.25 no.4
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• pp.13-26
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• 2019

The rural areas in South Korea have changed rapidly in the process of national land development. Rural landscapes have become discoloured, and their attractiveness has decreased as cities have expanded. But the attractiveness or multifunctional values of rural areas has become more important in contemporary society around the world. According to this social demand, the efforts of conserving the rural landscape are of high priority and the recovery of ruralism in the area is required. This study has tried to understand how the public image of ruralism in South Korea has been influenced by the news media. The study retrieved news articles using the web searching portal site from the six keywords, commonly used to refer to ruralism, including 'rural landscape', 'rural community', 'rural tourism', 'rural life', 'rural amenity', and 'rural environment'. News data from the six keywords were also collected respectively from within the year-period of 2004-05, 2007-08, 2012-13, and 2016-17. In the text mining analysis, the nouns with high Degree Centrality were figured out, and the changes by year-period were identified. Then, LDA topic analysis was performed for text datasets of six keywords. As a result, the study found that the news articles gave an informed focus on only a handful of issues such as 'poor rural living condition', 'regional or village improvement projects', 'rural tourism promotion projects', and 'other government support projects'. On the other hand, nouns related to virtues and values in the rural landscape were less shown in news articles. These results have become more apparent in recent years. In the topic analysis, 35 topics were identified. 'village development projects', 'rural tourism', and 'urban-rural exchange projects' were appeared repeatedly in several keywords. Among the topics, there are also topics closely related to ruralism such as 'rural landscape conservation', 'eco-friendly rural areas', 'local amenity resources', 'public interest values of agriculture', and 'rural life and communities'. The study presented an image map showing ruralism in South Korea using a network map between all topics and keywords. At the end of the study, implications for Korean rural area policy and research directions were discussed.

• 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.

• Korean Journal of Legislative Studies
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• v.24 no.2
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• pp.67-99
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• 2018

This study analyzes the revision bills of the National Assembly Law in the 19th National Assembly in which the National Assembly Advancement Act was enacted, with the question "who are involved in the revision of the procedural rules, and what motivates them?" The cosponsor network analysis focusing on primary sponsors of the revision bills shows that the network was constructed by party affiliations. A small number of members with high degree centrality attempted to cooperate with each other at the cosponsoring stage, but the legislation did not pass through the related committee. In addition, this study tests the four competitive hypotheses (the committee hypothesis, the distributive politics hypothesis, the ideological distance hypothesis, and the partisan affiliation hypothesis) about the motivation to propose amendments by using the regression models which include newly measured variables. Only the committee hypothesis and the partisan affiliation hypothesis are empirically supported. This implies that partisan consideration is still significant in amending the National Assembly Law even after the National Assembly Advancement Act, and thus party leaders' willingness to seek bipartisan compromises is at the heart of problem-solving.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.3
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• pp.89-108
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• 2022

The purpose of this study is to reveal the specific current and future shapes of the collaborative network among organizations witch cope the COVID-19 in Korea. For this, this study conducted social network analysis, based on the response data of 73 experts from 36 COVID-19-related organizations. As a result of the analysis, it was confirmed that the Korea Disease Control and Prevention Agency (KDCA) plays a pivotal role as a control tower in coping COVID-19 in all of the analysis of degree, betweenness, and closeness centrality. In addition, the results revealed concrete forms of collaborative relationships among participating organizations in the public and private sectors that constitute the present and future networks centered on the KDCA. Furthermore, this study presented which organizations and relationships should be the focus of establishing a future collaborative network through comparative analysis between the current cooperative network and the network to be built in the future. The analysis results and discussions of this study are expected to be used as useful information for policy development related to collaborative networks that can effectively respond to disasters caused by new diseases in the future.

• Journal of Technology Innovation
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• v.21 no.1
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• pp.279-301
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• 2013

This study demonstrates how social network analysis can be used for identifying potential buyers in technology marketing; in such, the methodology and empirical results are proposed. First of all, we derived the three most important 'seed' keywords from 'technology description' sections. The technologies are generated by various types of R&D activities organized by South Korea's public research institutes in the fundamental science fields. Second, some 3, 000 words were collected from websites related to the three 'seed' keywords. Next, three network matrices (i.e., one matrix per seed keyword) were constructed. To explore the technology network structure, each network is analyzed by degree centrality and Euclidean distance. The network analysis suggests 100 potentially demanding companies and identifies seven common companies after comparing results derived from each network. The usefulness of the result is verified by investigating the business area of the firm's homepages. Finally, five out of seven firms were proven to have strong relevance to the target technology. In terms of social network analysis, this study expands its application scope of methodology by combining semantic network analysis and the technology marketing method. From a practical perspective, the empirical study suggests the illustrative framework for exploiting prospective demanding companies on the web, raising possibilities of technology commercialization in the basic research fields. Future research is planned to examine how the efficiency of process and accuracy of result is increased.