Establishment of efficient cooperative ecosystem of research institutes is important for the efficiency of national innovation system, especially in the era of technology convergence. Performance of institutes inside the ecosystem is dependent on the position of the institutes in the system. This study investigates the relationship between network structure and research performance, and determines significant factors on the research performance. The results of 5 year panel data analysis of SCI journal papers of Korean government research institutes indicate that four network centralities -degree, betweenness, closeness, and eigenvector- and structural holes have significant effect on the research performance of the institutes. Among the four centralities, closeness and eigenvectors are more significant than others. Implications of the results of this study for policy of establishing efficient cooperative system are that increasing the cooperative activities of less active institutes is more effective for research performance than increasing the magnitude of cooperative activities of all institutes. Also, when an institute starts a new cooperative relationship, it is better to have relationship with an active institute first.
Journal of The Korean Association For Science Education
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v.38
no.4
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pp.565-574
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2018
The purpose of this study is to investigate the features of science classes of Science Core Schools (SCSs) perceived by students. 654 students from 14 SCSs were surveyed with two open-ended questions on the features of science classes. The students' responses were analyzed with NetMiner 4.5, in terms of the centrality (of betweenness and of degree) analysis and the community analysis. The results of the research are as follows: (1) the science classes of SCSs were perceived by students to be of the environment of free questioning, active participation and communication, caring teacher, more science experiments and advanced contents, and knowledge sharing; (2) science classes in SCSs were perceived to be different from those of ordinary high schools because SCSs provide more opportunities for science-related special courses (like project work, advanced science subjects), extra-curricular activities, inquiry and research activities, school supports, hard-working classroom environment, longer studying hours, R&E and club activities. The students' perceptions of SCS science classes appear to be in line with the characteristics of 'good' science lessons from previous studies. The SCS project itself and the features of SCS science classes would help us to see how we introduce educational innovations into actual schools.
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.
Ha, Ki Mok;Moon, Hyun Sil;Choi, Il Young;Kim, Jae Kyeong
Journal of Intelligence and Information Systems
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v.20
no.2
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pp.1-17
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2014
The proliferation of using social media and social networking services affects the lifestyles of people. These phenomena are useful to companies that wish to promote and advertise new products or services through these social media; these social media venues also come with large amounts of user data. However, studies that analyze the data of social media within the perspective of information exchanges are hard to find. Much of the previous research in this area is focused on measuring the performance of exhibitions using general statistical approaches and piecemeal measures. Therefore, in this study, we want to analyze the characteristics of information exchanges in social media by using Twitter data sets, which are relating to the Mobile World Congress (MWC). Using this methodology provides exhibition organizers and exhibitors to objectively estimate the effect of social media, and establish strategies with social media use. Through a user network analysis, we additionally found that social attributes are as important as the popular attribute regarding the sustainability of information exchanges. Consequently, this research provides a network analysis using the data derived from the use of social media to communicate information regarding the MWC exhibition, and reveals the significance of social attributes such as the degree and the betweenness centrality regarding the sustainability of information exchanges.
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.
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.
The purpose of this study was to analyze the perceptions of disabled sports that were reported the newspapers using semantic network analysis method. for this purpose, 745 news articles were selected from 21 source in Naver news searching engine. The main keyword for searching on newspapers was 'disabled sports'. Krkwic software was used for keyword cleansing and co-occurrence of text to text matrix in frequencies. Centrality indices that are degree, between and eigenvector, were used to analyze the perceptions of disabled sports from Netminer 4.0 for semantic network analysis. The conclusion of overall results from this study are follows; First, the core keyword of disabled sports in newspapers are 'impression', 'challenge', 'festival', 'dream' and hope. And there is different concepts of cognition among types of disability. Second, there are two elements on the perceptions of disabled sports from reported newspapers; sports performance and emotional. Specifically, main stream of keyword were 'Paralympics' and 'Special Olympics' on sports performance element and 'impressive' and 'challenge' in emotion element.
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 the Korea Society of Computer and Information
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v.28
no.1
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pp.189-199
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2023
This study aimed to identify the development direction of Arduino-based boards relating to artificial intelligence based on social awareness identified using big data analytical methods. For the purpose, big data were extracted through the Textom website, focusing on keywords that included 'Arduino + artificial intelligence' and 'Arduino + AI', and these data were refined and analyzed using the Textom website and the UNICET program. In this study, big data analyses, including frequency analysis, TF-IDF analysis, Degree Centrality analysis, N-gram analysis, and CONCOR analysis, were performed. The analyses' results confirmed that keywords relating to education and coding education, keywords relating to making and experience based on Arduino, and keywords relating to programs were the main keywords used in Arduino- and artificial intelligence-related Internet documents, and clusters were formed based on these keywords confirmed. The social awareness of Arduino and artificial intelligence was evaluated, and the direction of board development was identified based on this social awareness. This study is meaningful in that it identified various factors of board development based on the general public's social awareness, which was evaluated using a big data analysis method. This study may serve as a point of reference for future researchers or developers wishing to understand user needs using big data analysis methods.
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.
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