• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2013.06a
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• pp.146-148
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• 2013

본 연구는 지속가능한 물류활동에서 관심을 받고 있는 내항해운(연안해운)의 물류네트워크를 파악하기위한 기초분석으로서 연안여객항로에 관하여 네트워크를 파악하였다. 최근에 기존의 계량적 통계분석방법을 뛰어넘어 존재하고 있는 구조와 실체를 파악하기위해 사회연결망분석이 도입되고 있는 상황에서, 우리나라 연안해운항로의 네트워크를 파악하고자 하였다. 내항해운은 화물운송과 여객운송으로 구별되나 본 연구에서는 화물선만 고려하였다. 국가물류통합정보센터와 해운항만물류정보시스템을 활용하여 한국의 내항해운의 중심성을 분석하였다. 중심성 분석을 위해서 화물선 출입항 척수와 화물처리량을 변수로 사용하여 Pajek과 UCINET 등의 SNA 프로그램을 이용한 결과 내항해운 네트워크를 도식화하고 파악하였다. 결과적으로 네트워크의 node에 해당하는 항만 중에서 어떤 항만이 가장 중요한 노드인지를 찾고, 네트워크 구조가 얼마나 소수의 중요한 항만에게 집중되는 것인지를 확인하기 위하여 중심성 분석을 통해 파악하였다.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.27 no.3
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• pp.151-171
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• 2016

This study investigated the contents of twitters of metropolitans by year and city using language network analysis. The possibility of twitter as a medium of information provision was also explored. This study employed KrKwic, Ucinet6, and Netdraw programs to conduct language network analysis. As the results, the network was mainly formed with information about civic administration (citizen, management, opening service, participation) and information about citizens living (cultural events, parks, way to work) in 2014. However, information about civic service and announcement (citizen, civic opinion, opening service, civic service, events) occupied a central role in the network of 2015. The results showed that different keywords were derived by year and city in network analysis by city.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.222-230
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• 2023

The purpose of this study is to provide basic data on sports entertainment programs by collecting data on unstructured data generated by Naver and Google for SBS entertainment program 'Women Who Score Goal', which began regular broadcast in June 2021, and analyzing public perceptions through data mining, semantic matrix, and CONCOR analysis. Data collection was conducted using Textom, and 27,911 cases of data accumulated for 16 months from June 16, 2021 to October 15, 2022. For the collected data, 80 key keywords related to 'Kick a Goal' were derived through simple frequency and TF-IDF analysis through data mining. Semantic network analysis was conducted to analyze the relationship between the top 80 keywords analyzed through this process. The centrality was derived through the UCINET 6.0 program using NetDraw of UCINET 6.0, understanding the characteristics of the network, and visualizing the connection relationship between keywords to express it clearly. CONCOR analysis was conducted to derive a cluster of words with similar characteristics based on the semantic network. As a result of the analysis, it was analyzed as a 'program' cluster related to the broadcast content of 'Kick a Goal' and a 'Soccer' cluster, a sports event of 'Kick a Goal'. In addition to the scenes about the game of the cast, it was analyzed as an 'Everyday Life' cluster about training and daily life, and a cluster about 'Broadcast Manipulation' that disappointed viewers with manipulation of the game content.

• Korean Journal of Comparative Education
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• v.24 no.3
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• pp.227-244
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• 2014

This study is to explore and compare the main research area of national and international universities, figure out the differences of the research trends depending on national and international universities, and suggest which area Korea universities could focus on and head to. The study is conducted on the fields of 'Communication and Media' in humanities and 'Electrical Engineering' in engineering for the cases of 10 national and international universities. The data is based on the 3 years journals published between 2009 and 2011 by 10 universities, and analyzed using network analysis. The data is processed with three steps and visualized using Ucinet, Gephi, Netdraw program. These result show, in case of 'Communication and Media', the focus of the universities in Korea mainly on the classical research fields with only a few new research area comparing with international universities. In case of 'Electrical Engineering', national and international universities covers various areas, from classic ones to emerging ones. But the specific research areas are different. These results suggest the research areas which ares the universities in Korea will pursue in near future.

• Journal of Korea Entertainment Industry Association
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• v.13 no.8
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• pp.377-389
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• 2019

This study conducted social network big data analysis to investigate consumer's perception of Japanese sporting goods related to Japanese boycott and to extract problems and variables by recognition. Social network big data analysis was conducted in two areas, "Japanese boycott" and "Japanese sporting goods". Months of data were collected and investigated. If you specify the research method, you will identify the issues of the times - keyword setting using social network analysis - clustering using CONCOR analysis using TEXTOM and Ucinet 6 programs - variable selection through expert meetings - questionnaire preparation and answering - and validity of questionnaire Reliability Verification - It consists of hypothesis verification using the structural model equation. Based on the results of using the big data of social networks, four variables of relevant characteristics, nationality, attitude, and consumption behavior were extracted. A total of 30 questions and 292 questionnaires were used for final hypothesis verification. As a result of the analysis, first, the boycott-related characteristics showed a positive relationship with nationality. Specifically, all of the characteristics related to boycotts (necessary boycott, sense of boycott, and perceived boycott benefits were positively related to nationality. In addition, nationality was found to have a positive relationship with consumption behavior.

• Journal of Korea Entertainment Industry Association
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• v.13 no.4
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• pp.173-184
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• 2019

The data processing of this study is based on the word data search in social media through textom and the big data analysis is carried out and three areas (2019 Gwangju World Swimming Championships, 2019 Gwangju World Swimming Masters Competition, 2019 World Swimming Championships Problem) was consistently handled through data collection and refinement in the web environment. We applied the collected words to the program of Ucinet6, visualized them, and conducted a CONCOR analysis to grasp the similar relationship of words and to identify the cluster of common factors. As a result of the analysis, the clusters related to the 2019 Gwangju World Swimming Championships mainly consisted of four major areas of recognition and perception, mainly searching for operational aspects related to the swimming championship, and the community related to the 2019 Gwangju World Swimming Masters Competition Is mainly searched for the promotion of the Masters Competition and the aspect of the competition divided into two areas of major recognition and peripheral recognition. The cluster related to the problems of the 2019 Gwangju World Swimming Championships is divided into five areas, And they are mainly searching for the place, operation, institution, event, etc. of the problem of the swimming championship.

• Journal of Digital Convergence
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• v.16 no.9
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• pp.437-442
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• 2018

The study aims to identify key players through the last five passes when entering shooting circles in Korea and top four countries participated in the Rio Olympics. First, the analysis code was created using the Sports code to analyze the 29 games including Korea and the top 4 countries among 33 games. Second, Ucinet 6 has been used to analyze the Closeness Centrality of each country. The results of the study show that Korea is a key player in No.13 FW, New Zealand in No.1 MF, Germany in No.5 DF, Netherlands in No.9 MF and U.K in No.8 MF. In particular, the two teams that advanced to the finals saw their proximity center index average over 60. Based on these results, it is expected that the analysis of women's field hockey matches will serve as a tool to identify key players.

• The Journal of the Korea Contents Association
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• v.20 no.6
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• pp.187-196
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• 2020

This study attempted to examine the structural characteristics of the social network of nursing units by dividing them into a job-related advice network and a friendship network, and to analyze the relationship between nurse organizational commitment and intent to leave. The subjects were 420 nurses working in 4 hospitals and 30 nursing units. Data were analyzed using UCINET 6.0, SPSS 20.0 and HLM 7.0. In job-related advice networks, degree centrality of head nurse contributed to organizational commitment. Network density contributed to intent to leave. In friendship networks, closeness centrality of head nurses and betweenness centrality of charge nurse contributed to organizational commitment. Density and betweenness centrality of charge nurses contributed to intent to leave. Accordingly, it is necessary to foster good relationships between nurses and to develop various types of strategies for building effective networks.

• Journal of the Korean earth science society
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• v.34 no.2
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• pp.148-161
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• 2013

The purpose of the study was to investigate the relationship between the communication status in group and the semantic network of science gifted students. Seven small groups, 5 members in each, participated in small group activities, in which they discussed the calculation of earth density. Both the communication status in group and the semantic network of science gifted students were analyzed using KrKwic, Ucinet 6.0 for Windows. As a result, the semantic network of prime movers in group represented more frequently used words, lesser rate of component, and higher density than that of out lookers. It means that the prime movers have coherent knowledge compared to out lookers, and they output more knowledge for problem solving than out lookers. Therefore, the results of this study may be applied to evaluating the cognitive level of science gifted students and group organization for small group activity.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.3
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• pp.1414-1423
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• 2014

This paper aims to analyze destination composition patterns included in package products and to identify the characteristics of the tourism destinations through social network analysis using data collected from tour packages distributed by major Korean travel agencies, targeting Singapore as a key destination. Such tour package data were transcribed into data matrix using Pajek, UCINET, and Cytoscape for analysis. The density and centralization scores derived from the analysis indicated clearly that each destination was almost connected to each other. The centrality scores indicated that the destinations with higher degree of centrality also has higher betweenness centrality within the network. Based on centrality scores, POI(point of interests) of tourism destinations showed concentration in southern area of the target region. Finally, through component analysis, subgroups of tourism destination networks are isolated. Practical implications were also presented for industry practitioners.