• Journal of Technology Innovation
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• v.29 no.1
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• pp.39-73
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• 2021

The cooperative network structure influences the academic performance of the research institute. In particular, South Korea's Government-Funded Research Institutes(GRI) need to establish an efficient cooperative system as a leading national R&D implementer. This study applied the Small World structure, which has been discussed as an efficient network structure, and the centrality of representing the characteristics of nodes to the cooperative network of GRI in Korea. Based on the SCIE published data from 2010 to 2019, we analyze how the Small World characteristics and centrality of GRI contribute to academic performance using a network analysis and Feasible GLS regression. The GRI cooperative network has shown that the Small World network structure facilitates the academic performance. In addition, centrality indicating the degree of direct connection showed positive significance, but centrality indicating the degree of intermediary was not significant or negative. The results of this study explain that the higher the number of institutions that exchange and cooperate, the higher the academic performance, and the higher the performance of the institutions that serve as the center of cooperation. In addition, it was established that the stronger the cooperative network of GRIs have the characteristics of Small World, the more effective it is to create research results. This study applies centrality and Small World previously discussed as an efficient network structure to the GRI cooperation network and provide implications for establishing policies and strategies related to R&D cooperation among GRIs.

• Information Systems Review
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• v.22 no.1
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• pp.147-165
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• 2020

The sharing economy service is now spreading in various fields such as accommodation, cars and bicycles. In particular, bicycle-sharing service have become very popular around the world, and since September 2015, Seoul has been providing a bicycle-sharing service called 'Ttareungi'. However, the number of bicycles is unbalanced among rental stations continuously according to the user's bicycle use. In order to solve these problems, we employed social network analysis using Ttareungi data in Seoul, Korea. We analyzed degree centrality, closeness centrality, betweenness centrality and k-core. As a result, the degree centrality was found to be closely linked with bus or subway transfer center. Closeness centrality was found to be in an unbalanced departure and arrival frequency or poor public transport proximity. Betweenness centrality means where the frequency of departure and arrival occurs frequently. Finally, the k-core analysis showed that Mapo-gu was the most important group by time zone. Therefore, the results of this study may contribute to the planning of relocation and additional installation of bike rental station in Seoul.

• Information Systems Review
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• v.20 no.3
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• pp.1-16
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• 2018

MICE (Meetings, Incentive trip, Convention and Exhibition & Event) industry is a multifaceted industry with a variety of stakeholders including the public and private sectors, and PCOs (Professional Convention Organizers) play a mediating role in communicating opinions of the stakeholders. For enhancing their reliability and awareness, PCOs have their stakeholders' hyperlinks on the websites. This study attempted to analyze the hyperlink networks among PCOs (Professional Convention Organizers) and their stakeholders so as to understand the MICE industry ecosystem and find out whether the network structure of PCOs' shows different levels of hyperlink use with their stakeholders' websites based upon PCO's performance and size. The results showed the hyperlink network of MICE industry and that the bigger PCOs have higher centralities in the network.

• Journal of Korea Port Economic Association
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• v.32 no.1
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• pp.97-122
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• 2016

Incheon port attained two million TEU of container throughput between 2013 and 2014 as a third port in domestic container throughput. It opened a new port in Song-do, Incheon in June 2015 to prepare for the continuing increase in container throughput.Therefore, it has provided the platform for being the major container port domestically and internationally. As the role of the new port increases, the role and direction of the Incheon port liner service network attracts attention. This study analyzes the centrality of the Incheon port liner service network by using SNA (Social Network Analysis), which was introduced in the maritime economics area recently, focusing on the Incheon port liner service network. We recognize the degree centrality, closeness centrality, and betweenness centrality of each port and its effect on the Incheon port liner service network. The study showed that for Incheon port, the centrality of the Busan port in Korea, and the Hong Kong port, is high outside the country. This helps us determine that the hub of the Incheon port is neither Shanghai nor Singapore, which ranks first and second, respectively, on container throughput. It is also helps us to know that eastern China's ports have not played a role of the hub of the Incheon port until now because of the relatively low centrality of eastern China's ports.

• The KIPS Transactions:PartB
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• v.18B no.5
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• pp.279-290
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• 2011

As the volume of internet and web contents have shown an explosive growth in recent years, lately contents recommendation system (CRS) has emerged as an important issue. Consequently, researches on contents recommendation method (CRM) for CRS have been conducted consistently. However, traditional CRMs have the limitations in that they are incapable of utilizing in web 2.0 environments where positions of content creators are important. In this paper, we suggest a novel way to recommend web contents of high quality using both degree of centrality and TF-IDF. For this purpose, we analyze TF-IDF and degree of centrality after collecting RSS and FOAF. Then we recommend contents using these two analyzed values. For the verification of the suggested method, we have developed the CRS and showed the results of contents recommendation. With the suggested idea we can analyze relations between users and contents on the entered query, and can consequently provide the appropriate contents to the user. Moreover, the implemented system we suggested in this paper can provide more reliable contents than traditional CRS because the importance of the role of content creators is reflected in the new system.

• Journal of the Korea Convergence Society
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• v.9 no.2
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• pp.251-257
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• 2018

As the use of big data is necessary for increasing business value, the size of the big data market is getting bigger. Accordingly, it is important to apply competitive patents in order to gain the big data market. In this study, we conducted the patent analysis based keyword network to analyze the trend of big data patents. The analysis procedure consists of big data collection and preprocessing, network construction, and network analysis. The results of the study are as follows. Most of big data patents are related to data processing and analysis, and the keywords with high degree centrality and between centrality are "analysis", "process", "information", "data", "prediction", "server", "service", and "construction". we expect that the results of this study will offer useful information in applying big data patent.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.648-654
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• 2016

This paper investigates differences of tourism destination choices for sightseeing in Seoul between first-time visitors and repeat visitors. We constructed social network using secondary data from '2015 International Visitor Survey' and analyzed its density and centrality. Study results find that: (1) first-time and repeat visitors' tourism destinations are concentrated in areas located north of the Han river. The proximity of destinations suggests the positive effects resulting from the movement network. (2) As the result of degree centrality, closeness centrality, betweenness centrality, the highest ranking tourism destinations for both visitor groups are identical, but indexes of centralities in repeat visitors' destinations increase, including Shinchon/ Hongik University, Gangnam station, and Garosu-gil. Therefore, the roles of these destinations are becoming established as tourism hubs and are popular among younger visitors as well as attract repeat visitors. Results of this study will be a useful reference in developing and managing new tourism products.

• Korean Journal of Social Welfare Studies
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• v.41 no.4
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• pp.313-343
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• 2010

The aim of this study is to examine the factors influencing network centrality on women's welfare organizations, and to investigate how the level of network centrality influence the effectiveness of the organization. To achieve this goal, this study conducted a survey on women's welfare organizations in Seoul from March to June, 2009. Network analysis method was used to get each organization's network centrality value. Also, through the Structural Equation Modelling, organizational characteristics predicting network centrality and effect of network centrality on organizational effectiveness. The main results are as follows. First, the significant affecting factors were different between three types of centralities with regards to the type of organization, recognition of resource dependency, attitude of top manager, and established year. Second, the common factors affecting three network centralities were the number of informal ties, accepting feminism as the main organizational philosophy, and the number of qualified staffs. Third, only closeness centrality positively predicted the level of organizational effectiveness among three types of centralities. The faster the organization reaches to other organizations in a network, the organizational effectiveness becomes higher, which means high closeness centrality is more important factor than high degree centrality or high betweenness centrality to increase organizational effectiveness. This result shows social welfare organization should consider changing inter-organizational network strategy from quantity-focused to quality-focused.

• Journal of the Korea Society of Computer and Information
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• v.26 no.5
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• pp.103-110
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• 2021

The purpose of this study is to check the trend of press articles and research trends in journal papers in the last 10 years, which dealt with the subject of 'university core competencies' with a big data analysis method. The main research methodology of this study applied the BigKinds analysis system and the semantic network analysis methodology. The results are as follows: First, the number of press articles related to university core competencies showed a keyword trend that rapidly increased in December 2014 and the second half of 2020. Related keywords were curriculum, specialization, project group, Ministry of Education, ACE, and competitiveness. Second, the semantic network value between keywords of related research papers showed 554 degree, 18,467 avg. degree, and 0.637 density. The degree of centrality of connection was analyzed in the order of university(1606), competency(1481), core(1349), and core competency(1301). Betweenness centrality was analyzed as core competencies(13.101), university students(13.101), university(13.101), and competencies(13.101). The results of this research are expected to give implications to future research and policy-making, educational program planning and operation, etc. to members of higher education institutions, experts in education policy, and educational scholars.

• Journal of Korean Library and Information Science Society
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• v.47 no.4
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• pp.1-18
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• 2016

The purpose of this study is to explore application of topic modeling for topic analysis of book report. Topic modeling can be understood as one method of topic analysis. This analysis was conducted with texts in 23 book reports using LDA function of the "topicmodels" package provided by R. According to the result of topic modeling, 16 topics were extracted. The topic network was constructed by the relation between the topics and keywords, and the book report network was constructed by the relation between book report cases and topics. Next, Centrality analysis was conducted targeting the topic network and book report network. The result of this study is following these. First, 16 topics are shown as network which has one component. In other words, 16 topics are interrelated. Second, book report was divided into 2 groups, book reports with high centrality and book reports with low centrality. The former group has similarities with others, the latter group has differences with others in aspect of the topics of book reports. The result of topic modeling is useful to identify book reports' topics combining with network analysis.