• Journal of Life Science
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• v.26 no.8
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• pp.904-910
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• 2016

Complex traits are determined by the combined effects of many loci and are affected by gene networks or biological pathways. Systems biology approaches have an important role in the identification of candidate genes related to complex diseases or traits at the system level. The gene network analysis has been performed by diverse types of methods such as gene co-expression, gene regulatory relationships, protein-protein interaction (PPI) and genetic networks. Moreover, the network-based methods were described for predicting gene functions such as graph theoretic method, neighborhood counting based methods and weighted function. However, there are a limited number of researches in livestock. The present study systemically analyzed genes associated with 102 types of economic traits based on the Animal Trait Ontology (ATO) and identified their relationships based on the gene co-expression network and PPI network in cattle. Then, we constructed the two types of gene network databases and network visualization system (http://www.nabc.go.kr/cg). We used a gene co-expression network analysis from the bovine expression value of bovine genes to generate gene co-expression network. PPI network was constructed from Human protein reference database based on the orthologous relationship between human and cattle. Finally, candidate genes and their network relationships were identified in each trait. They were typologically centered with large degree and betweenness centrality (BC) value in the gene network. The ontle program was applied to generate the database and to visualize the gene network results. This information would serve as valuable resources for exploiting genomic functions that influence economically and agriculturally important traits in cattle.

• Journal of Korean Library and Information Science Society
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• v.50 no.1
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• pp.23-41
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• 2019

This study understand the subject domain of book which has been read by men and woman elderly by analizying the PFNET using library big data and confirm the difference between adult at age 30-40. This study extract co-occurrence matrix of book lending on the popular book list from library big data, for 4 group, men/woman elderly, men/woman adult. With these matrix, this study performs FP network analysis. And Pearson Correlation Analysis based on the Triangle Betweenness Centrality calculated on the loan book was performed to understand the correlation among the 4 clusters which has been created by PNNC algorithm. As a result, reading trend which has been focused on modern korean novel has been revealed in elderly regardless gender, among them, men elderly show extreme tendency concentrated on modern korean long series novel. In the correlation analysis, the male elderly showed a weak negative correlation with the adult male of r = -0.222, and the negative direction of all the other groups showed that the tendency of male elderly's loan book was opposite.

• The Journal of Society for e-Business Studies
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• v.21 no.2
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• pp.23-46
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• 2016

With the increasing socio-economic value of an open collaboration over the Internet, it has become significantly important to successfully manage open source software development program. Most of the previous research have focused on various factors that influence the performance of the project, but studies on how the project owners recognized as "leader" affect the outcome of the project are very limited. This research investigates how individual and governance characteristics of an owner influences the performance of project based on impression formation and social capital theory. For a data set, we collect 611 Repositories and the owner's data from the open source development platform Github, and we form knowledge sharing network of an each repository by using social network analysis. We use hierarchical regression analysis, and our results show that a leader, who exposes a lot of one's personal information or who has actively followed and showed interests to communicate with other developers, affects positive impacts on project performance. A leader who has a high centrality in knowledge sharing network also positively affects on project performance. On the other hand, if a leader was highly willing to accept external knowledge or is recognized as an expert in the community with large numbers of followers, the result show negative impacts on project performance. The research may serve as a useful guideline not only for the future open source software projects but also for the effective management of different types of open collaboration.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.728-739
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• 2020

Using webometric big data, this study examines the diversity of online information sources about the novel coronavirus causing the COVID-19 pandemic. Specifically, it focuses on some 28 countries where confirmed coronavirus cases occurred in February 2020. In the results, the online visibility of Australia, Canada, and Italy was the highest, based on their producing the most relevant information. There was a statistically significant correlation between the hit counts per country and the frequency of visiting the domains that act as information channels. Interestingly, Japan, China, and Singapore, which had a large number of confirmed cases at that time, were providing web data related to the novel coronavirus. Online sources were classified using an N-tuple helix model. The results showed that government agencies were the largest supplier of coronavirus information in cyberspace. Furthermore, the two-mode network technique revealed that media companies, university hospitals, and public healthcare centers had taken a positive attitude towards online circulation of coronavirus research and epidemic prevention information. However, semantic network analysis showed that health, school, home, and public had high centrality values. This means that people were concerned not only about personal prevention rules caused by the coronavirus outbreak, but also about response plans caused by life inconveniences and operational obstacles.

• 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.

• Korean Journal of School Psychology
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• v.18 no.1
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• pp.31-48
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• 2021

The purpose of this study was to determine whether the retention of university freshmen could be predicted using their peer relationships in a specific department. In this study, retention was defined as a student staying enrolled in their university for a certain period of time. Social relationships are formed through interaction between people, so both students' self-perceptions and others' perceptions of them must be accounted for, so we used a social network analysis that did so. We examined social networks visualizations that allowed for a rich interpretation of numerical information. Participants in this study were freshmen who enrolled in an undergraduate program in 2017, 2018, or 2019. We used the name generator method to determine how quantitative friendship network variables predicted the academic retention up to the first semester of 2020. Cox proportional hazard model analysis showed that the weighted indegree centrality with intimacy positively predicted retention. The results of this study can be used to identify and conduct interventions for students who may be likely to disenroll. However all of the students did not participate in the department, it was difficult to examine their entire peer networks. Thus, this study's results cannot be generalized because the participants are students of a specific major, so further research is needed to produce more generalizable results.

• Journal of Internet of Things and Convergence
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• v.3 no.2
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• pp.33-39
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• 2017

The purpose of this study is to analyze the characteristics of talents required in electronic companies in the 4th industrial revolution. we conducted a network analysis on the key talent of the companies presented in over 100 job announcements to companies in the electronics industry. The results of the study are as follows. First, electronic companies showed the most favored creative talents, preferring collaborative talent and challenging talent. Second, looking at the core definitions of talent, change, response, problem solving, performance creation, communication, challenge, professionalism, enthusiasm, development, aggressiveness and spontaneity were used. In other words, key keywords emerging from the 4^th industrial revolution were being used continuously. Third, in the Centrality analysis, talented people who emphasize humanity also appeared. Based on the study, it suggested that manpower training of the 4^th Industrial Revolution.

• Journal of Korea Technology Innovation Society
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• v.15 no.3
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• pp.722-743
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• 2012

Confronted with increasing global competition and rising research and development risks, the global open innovation has receiving increased attention. This study empirically investigates whether or not international cooperative R&D is effective by evaluating the quality indicators with the patents with international co-applications. The number of patents with international co-applications has dramatically increased in recent years. According to the results, the outcome from international cooperative R&D is prominent in term of all the evaluation criteria such as the number of citation, patent families, claims, and et cetera, compared with that from domestic cooperative R&D. Based on the patent quality, the information technology sector holds the top spot and high-tech sectors such as bio and automobile industries show the better quality performances. By identifying high betweeneess centrality in the network analysis of international cooperative R&D, the US is indicated as the most central country in such cooperative activity, and then Germany, the UK, Canada, and France come after.

• The Journal of the Korea Contents Association
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• v.12 no.12
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• pp.661-671
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• 2012

The purpose of this study was to analyze the core policies of local government directors by performing centrality analysis on their core policies using network text analysis method. From the research results, it was verified to some extent that major policies of local government directors were changing during the path to arrive at 5th civil election. However, according to policy type by Peterson (development policy, allocation policy and redistribution policy) it was found that they still focused on development policies. However, it is encouraging that the government directors elected in the 5th election started to pay attention to 'Culture' which is one of allocation policies.

• Health Communication
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• v.12 no.1
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• pp.51-72
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• 2017

Purpose: Adolescents use emoticons to express their emotions in an online environment. Hence, medical experts can understand the emotions of adolescents by emoticons. The goal of this study was to investigate the relationship between various emotions and emoticons among the Korean adolescents. Methods: The questionnaire survey was conducted between September 1 and 30, 2014, involving 3,272 students in elementary schools, middle schools, and high schools affiliated in the Department of Education of the metropolitan city of Busan. A total of 1,717 students responded to the survey. The participants consisted of 806 males (46.9%), and 911 females (53.1%). Among these, there were 557 elementary school students (32.4%), 617 middle school students (35.9%), and 543 high school students (31.6%). A social networking analysis was conducted using NodeXL. Results: The frequency of emoticon use among adolescents runs in the order of joy, sadness, fear, surprise, anger, disgust, and then depression. Elementary school females mainly use emoticons to express joy; middle school females use emoticons to express sadness, surprise, anger, disgust, and depression; and high school females use emoticons to express fear. Age- and gender-specific emoticon networks were visualized by using the Haren-Korel fast multiscale algorithm. Commonly used emoticons by age and gender were expressed in the networks. Results of age- and gender-specific emoticon networks visualization show similar results of centrality of seven emoticons. Conclusion: In the digital communication environment, emoticons could be used to catch the emotions of adolescents in Korea.