• The Journal of the Korea Contents Association
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• v.8 no.4
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• pp.155-163
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• 2008

This study is to examine the cooperation plan of participating bodies in the area on social welfare system that is appropriate in the localization era. In order words, in order to develop the local social welfare system by approaching on the cooperation within the participating bodies within the area in the local governance level, the purpose of this study is to find out the problems that the existing local community welfare system has, and seek the responsive development cooperation plan. Furthermore, through this study, it is expected to present desirable cooperation model of local social welfare, and the reasonable welfare plan on the locality would be available.

• Journal of the Korean Geographical Society
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• v.49 no.1
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• pp.57-76
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• 2014

Conventional treatments of war diffusion focus extensively on dyadic relationships, whose impact is thought to be immutable over the course of the conf lict. This study indicates that such conceptions are at best incomplete, and more likely misleading to explain the spatial diffusion of wars. Using social network analysis, we examine war joining behavior during World War I. By employing social network analysis, we attempted to overcome the dichotomous understanding of geography as space and network in the discipline of conflict studies. Empirically, networked structural elements of state relationships (e.g., rivalry, alliances) have explanatory and predictive value that must be included alongside dyadic considerations in analyzing war joining behavior. In addition, our analysis demonstrates that the diffusion of conflict involves different driving forces over time.

• The Journal of Bigdata
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• v.6 no.1
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• pp.1-12
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• 2021

The rapid growth of mobile-based online shopping and the appearance of untact business initiated by COVID-19 has led to an explosive increase in demand for logistics services such as delivery services. In order to respond to the rapidly growing demand, most logistics and distribution companies are working to improve customer service levels through the establishment of a full-filament center in the city center. However, due to social factors such as high land prices and traffic congestion, it becomes more difficult to establish the logistics facilities in the city center. In this study, it has been proposed the way to choose the candidate locations for the shared distribution centers among the space nearby the tall-gate which can be idle after the smart tolling service is widely extended. In order to evaluate the candidate locations, it has been evaluated the centralities of all candidates using social network analysis (SNA). To understand the result considering the characteristics of centrality, the network structure was regenerated based on the distance and the traveling time, respectively. It is possible to refer the result of evaluation based on the cumulative relative importance to choose the best set of candidates.

• Korean journal of communication and information
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• v.19
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• pp.239-264
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• 2002

The networking between the press and elites, and its impact on journalistic activities in fact have been major subjects of scholarly scrutiny particularly among students of elite theory and class theory. This is an empirical analysis of how the press establishes networks with several powers in local community. This study basically examines a set of independent variables, such as the nature of capital and history of local newspapers and explores how the management and elites in the press utilize several social resources and establish networks. Major findings of this study are as follows: To begin with, the networking between local newspapers and elites showes significant differences according to the nature of capital and history of the newspaper. In other words, while the newspapers operated by stock capital revealed high degree of networking with political and financial elites, the newspapers operated by family capital did not demonstrate significant level of networking with particular elites. The shorter the history of newspaper is, the more she tends to be dependent on resources, and feel it imperative to establish strong networks with elites.

• The Journal of the Korea Contents Association
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• v.20 no.6
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• pp.482-497
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• 2020

The purpose of this study is to find out how college students overseas field trip group's social network exist, how the network change during the travel period, and how they are related to trip satisfaction, school involvement and peer relations. College students have an unprecedented school adaptation problem, which is questioning college education practices and measure should be taken. Since travel provides a strong bond with the group of participants, in a similar vein, students' overseas trips are also assumed to strengthen solidarity of students. For 31 trip participants, survey was administered to find out the existence of a distinctive network structure, its changes, and its impact on related variables. First, the network structure of the field trip existed explicitly, in which student representatives held their position in degree centrality. Second, network structure has changed before and after the trip, which is due to the social interaction between participants. Third, the effect on trip performance variables was marginal, even if some participants move to centrality. Forth, field trip satisfaction, school involvement, and peer relations were significant correlated. At the end of the paper, the implications and limitations of the study were included.

• Journal of Korean Home Economics Education Association
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• v.31 no.3
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• pp.73-90
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• 2019

The purpose of this study was to explore the differences in perceptions of male and female students about population problems and to draw up implications for population education. Using text mining, the report about population problem, which had written by students in population education class, were analysed. After extracting key words, semantic networks were visualized. The results were as follows. First, the high frequency words were the same for each gender. Second, key words based on frequency did not differ depending on gender. And the key words extracted by the correlation analysis and bigram were different. That is, in the semantic network of girls' words, the network of "life"-"marriage"-"birth"-"pregnancy" appeared independently, distinguishing it from male students who showed separate objective links to population problems. Therefore, it drew suggestions that male and female students should be viewed as heterogeneous groups with different cognitive structures on population problems and that the content and methods of population education should be approached differently depending on gender.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.465-476
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• 2020

This study used social network analysis to analyze trends and the knowledge structure of research in international trade. To this end, 4,840 keywords were extracted and analyzed from 1,797 papers contained in the Journal of Int'l Trade and Industry Studies, the Korea Trade Review, and the Journal of Korea Trade from 2003 to 2019. The results reveal that the distribution of keywords in the trade studies, as with other intellectual networks, followed a power-law distribution. Some differences were observed in the top 20 keywords across journals, with total factor productivity, economic growth, and Korea-US FTA ranking high only in the Journal of Int'l Trade and Industry Studies. Global value chain and trust emerged as a topic that attracted new researchers' attention in the 2011-2019 period. Interest in E-Trade, WTO, and internationalization has declined in recent years. The conventional international trade research trend analyses have predominantly featured qualitative analysis by descriptive method in general, but this study is meaningful in that it employs quantitative analysis using social network analysis techniques.

• The Journal of the Korea Contents Association
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• v.16 no.8
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• pp.160-168
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• 2016

The classification and evaluation of cooking that is being published on the internet are presented without scientific criteria based on individual subjective factors. In this paper, we objectified the degree of cooking difficulty based on the information entropy. And we measured the similarity by calculating the common entropy between recipes and constructed a social network based on the recipe similarity. As a result of measuring the cooking difficulty, 'Dongtae Haemul-jjim' (Korean) and 'Vegetarian Lasagna' (Italy) are the most difficult recipes and 'Gochu-jang' (Korean) and 'Tofu steak' (Italy) are the easiest recipes. Through the recipe network, the similarity between Korean and Asian cooking is higher than Western cuisine. We showed a similar recipe to a particular cooking, the group of similar recipes, and reasonable schedule when preparing the menu from the viewpoint of ease of cooking.

• The Journal of the Korea Contents Association
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• v.17 no.12
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• pp.49-63
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• 2017

Interdisciplinary convergence research is widely seen as a collaborative research between different disciplines, which is often driven by common agenda or problems in pursuit of a particular common objective. Thus, the purpose of interdisciplinary cooperation in convergence research is to bring each discipline's unique perspective together with the academic expertise of researchers in order to share common problems that cannot be solved effectively without research partnership. We present empirical evidence on how interdisciplinary research relationships are formed to facilitate research networking in convergence relations. In particular, we used network analysis to investigate how interdisciplinary linkages and convergence research networks has formed over time. We found that the convergence research networks were implemented by the interdisciplinary convergence research support program as intended. We did find that research field with high indegree and outdegree in a network played critical roles on the dynamics and degree of interdisciplinarity. Finally, we could find evidence that the role of liaison brokers triggered relational dynamics in interdisciplinary research collaboration.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.107-120
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• 2014

This study proposes a novel recommender system using the structural hole analysis to reflect qualitative and emotional information in recommendation process. Although collaborative filtering (CF) is known as the most popular recommendation algorithm, it has some limitations including scalability and sparsity problems. The scalability problem arises when the volume of users and items become quite large. It means that CF cannot scale up due to large computation time for finding neighbors from the user-item matrix as the number of users and items increases in real-world e-commerce sites. Sparsity is a common problem of most recommender systems due to the fact that users generally evaluate only a small portion of the whole items. In addition, the cold-start problem is the special case of the sparsity problem when users or items newly added to the system with no ratings at all. When the user's preference evaluation data is sparse, two users or items are unlikely to have common ratings, and finally, CF will predict ratings using a very limited number of similar users. Moreover, it may produces biased recommendations because similarity weights may be estimated using only a small portion of rating data. In this study, we suggest a novel limitation of the conventional CF. The limitation is that CF does not consider qualitative and emotional information about users in the recommendation process because it only utilizes user's preference scores of the user-item matrix. To address this novel limitation, this study proposes cluster-indexing CF model with the structural hole analysis for recommendations. In general, the structural hole means a location which connects two separate actors without any redundant connections in the network. The actor who occupies the structural hole can easily access to non-redundant, various and fresh information. Therefore, the actor who occupies the structural hole may be a important person in the focal network and he or she may be the representative person in the focal subgroup in the network. Thus, his or her characteristics may represent the general characteristics of the users in the focal subgroup. In this sense, we can distinguish friends and strangers of the focal user utilizing the structural hole analysis. This study uses the structural hole analysis to select structural holes in subgroups as an initial seeds for a cluster analysis. First, we gather data about users' preference ratings for items and their social network information. For gathering research data, we develop a data collection system. Then, we perform structural hole analysis and find structural holes of social network. Next, we use these structural holes as cluster centroids for the clustering algorithm. Finally, this study makes recommendations using CF within user's cluster, and compare the recommendation performances of comparative models. For implementing experiments of the proposed model, we composite the experimental results from two experiments. The first experiment is the structural hole analysis. For the first one, this study employs a software package for the analysis of social network data - UCINET version 6. The second one is for performing modified clustering, and CF using the result of the cluster analysis. We develop an experimental system using VBA (Visual Basic for Application) of Microsoft Excel 2007 for the second one. This study designs to analyzing clustering based on a novel similarity measure - Pearson correlation between user preference rating vectors for the modified clustering experiment. In addition, this study uses 'all-but-one' approach for the CF experiment. In order to validate the effectiveness of our proposed model, we apply three comparative types of CF models to the same dataset. The experimental results show that the proposed model outperforms the other comparative models. In especial, the proposed model significantly performs better than two comparative modes with the cluster analysis from the statistical significance test. However, the difference between the proposed model and the naive model does not have statistical significance.