• Title/Summary/Keyword: Analysis of Network Centrality

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Semantic Network Analysis of Research Trend Related to Private Security (언어 네트워크 분석(Semantic Network Analysis)을 활용한 민간경비 분야의 연구 경향)

  • Yang, Seung-Don
    • The Journal of the Korea Contents Association
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    • v.13 no.11
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    • pp.894-901
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    • 2013
  • This study is aim to research trend of private security and to suggest direction of improvement to sector of private security. This study has been to analyzed to be useful social network analysis(particularly Degree Centrality and Clossness Centrality) for using typical research method about trend of academic subject. As a result of Degree Centrality and Clossness Centrality, Individual factors such as Job Stress and Job satisfaction of private security are more keyword than institutional factors and policy factors such as Security Services Industry Act and training for Private Security guards. It means that research trend of private security are to study Individual factors rather than institutional factors and policy factors. But, this study is a limit as follows; First, An object of study is only to searching article in National Assembly Liberary. A follow-up studies are need to expand the range of an object of study for private security.

Network, Centrality, and Topic Analysis on Korea's Trade and Economy with Latin America and the Caribbean Area (한국의 중남미 지역연구 네트워크와 중심성 및 무역과 경제에 대한 토픽 변동분석)

  • Chae-Deug Yi
    • Korea Trade Review
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    • v.47 no.6
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    • pp.189-209
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    • 2022
  • This study aims to analyze Latin America and the Caribbean papers published in Korea during the past 2000-2020 years. Through this study, it is possible to understand the main subject and direction of research in Korea's Latin America and the Caribbean area. As the research mythologies, this study uses the text mining and Social Network Analysis such as frequency analysis, several centrality analyses, and topic analysis. After analyzing the empirical results, there has been a tendency to change the key words and centrality coefficients between 2000-2010 and 2011-2020 years. During 2011-2020 years, the most frequent keywords were changed from Neoliberalism and culture to policy education, and economy related words. The degree and closeness centrality analyses appeared the higher frequency key words. However, the eigenvector centrality appeared very different from the order of frequency key words. The topic analysis shows that the culture, language, and Neoliberalism were the most important keywords during 2000-2010 years but economy, labor trade, industry, development became the most important keywords during 2011-2020 years in topics.

A Study on the Relationship among Communication Competency, Social Network Centralities, Discussion Performance, and Online Boarding Activity in the Team Based Learning (팀 기반 토의 수업에서 의사소통능력, 사회연결망 중심도, 토론성과 및 온라인 게시활동의 관계 연구)

  • Heo, Gyun
    • Journal of Fisheries and Marine Sciences Education
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    • v.27 no.1
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    • pp.108-114
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    • 2015
  • The purpose of this study is to find the relationships among communication competency, social network centrality(trust centrality and knowledge sharing centrality), discussion performance, and online boarding activity in the team based learning situation. For investigating this topic, 44 students are participated in the classes of educational technology. In order to find out the relationships among communication competency, social network centrality, discussion performance, and online boarding activity, compared t-test and path analysis are used. Followings are the results of the research: (a) Communication competency is improved significantly after team based learning. (b) Trust centrality effects significantly on the knowledge sharing centrality. (c) Knowledge sharing effects significantly on discussion performance. (d) Trust centrality effects on the online boarding activity in the team based learning.

Study on Influence and Diffusion of Word-of-Mouth in Online Fashion Community Network (온라인 패션커뮤니티 네트워크에서의 구전 영향력과 확산력에 관한 연구)

  • Song, Kieun;Lee, Duk Hee
    • Journal of the Korean Society of Costume
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    • v.65 no.6
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    • pp.25-35
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    • 2015
  • The purpose of this study is to investigate the characteristics of members and communities that have significant influence in the online fashion community through their word-of-mouth activities. In order to identify the influence and the diffusion of word-of-mouth in fashion community, the study selected one online fashion community. Then, the study sorted the online posts and comments made on fashion information and put them into the matrix form to perform social network analysis. The result of the analysis is as follows: First, the fashion community network used in the study has many active members that relay information very quickly. Average time for information diffusion is very short, taking only one or two days in most cases. Second, the influence of word-of-mouth is led by key information produced from only a few members. The number of influential members account for less than 20% of the total number of community members, which indicate high level of degree centrality. The diffusion of word-of-mouth is led by even fewer members, which represent high level of betweenness centrality, compared to the case of degree centrality. Third, component characteristic shares similar information with about 70% of all members being linked to maximize information influence and diffusion. Fourth, a node with high degree centrality and betweenness centrality shares similar interests, presenting strain effect to particular information. Specially, members with high betweenness centrality show similar interests with members of high degree centrality. The members with high betweenness centrality also help expansion of related information by actively commenting on posts. The result of this research emphasizes the necessity of creation and management of network to efficiently convey fashion information by identifying key members with high level of information influence and diffusion to enhance the outcome of online word-of-mouth.

Investigating Good Teaching and Learning Experiences in the Perspectives of University Students through Social Network Analysis

  • OH, Suna;LYU, Jeonghee;YUN, Heoncheol
    • Educational Technology International
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    • v.21 no.2
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    • pp.193-216
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    • 2020
  • This study investigated university students' perspectives on good class and instructional practices through social network analysis. The subjects were 321 students in the third and fourth academic years in a Korean university. The subjects completed four open-ended questions, asking about experience of good class, good instructors' teaching practice, and their feelings and attitudes when participating in good class. As social network analysis, KrKwic (Korea Key Words in Context) was used to compute word frequencies and analyze semantic network structures and Ucinet Netdraw to assess centrality in the social network, consisting of degree centrality, closeness centrality, and between centrality. The results are as follows. First, students showed 5 keywords to depict what good class is, including 'understanding', 'example', 'video', 'interest', and 'communication'. Second, the characteristics of teaching methods by professors who practice good class indicate 'assignments', 'questions', 'understanding', 'example', and 'feedback'. Third, the top 5 keywords of students' attitudes as participating in good class are 'active', 'participation', 'focus', 'listening', and 'asking'. Last, keywords depicting desirable class that students most wanted to take next time are 'assignments', 'rewards', 'understanding', 'difficulty', and 'interest'. The findings from this study include the meanings of the semantic network structures of words in the text making up messages. Also this study can provide empirical evidence for educators and educational practitioners in higher education to create effective learning environments.

A Study on the Impact of Liner Shipping Network Characteristics to the World Regional Major Port performance (세계 주요지역 항만의 네트워크 특성이 성과에 미치는 영향에 관한 연구)

  • Kang, Dongjoon
    • Journal of Korea Port Economic Association
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    • v.31 no.4
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    • pp.189-207
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    • 2015
  • The purpose of this study is to examine the relationship between the network characteristics of ports and their performance that is represented by port competitiveness for the port operators. The study employs Social Network Analysis (SNA) to evaluate network characteristics comprising four centrality indices. For this research, data from Containerization International Yearbooks for 2006-2011 is used to analyze the service networks of 20 major liner shipping companies. In SNA, nodes (vertices) in the network are the ports and links (edges) in the network are connections realized by vessel movements, such that the liner shipping network determines the port network. In addition, panel regression analysis has been employed to investigate the relationship between port network characteristics and their performance. The results suggest that the four centrality indices identify the roles of the world's major ports from 2006 to 2011 and that port performance is determined not only by macroeconomic variables and service capabilities but also by the eigenvector centrality of ports in networks.

Relationship between Genre Centrality and Performance in the Motion Picture Industry (네트워크 중심성과 성과에 관한 연구: 영화산업을 중심으로)

  • Lee, Wonhee;Jung, Dong-Il
    • The Journal of the Korea Contents Association
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    • v.17 no.6
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    • pp.153-168
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    • 2017
  • Existing researches on movie genre have been focusing on the relationship between a specific genre and performance of a movie. However, most of films cross into multiple genres and new approach is needed for analyzing a genre network. In this study social network analysis was used to analyze the genre centrality and its relationship with movie performance by developing a genre network, i.e. network among multiple genres constructed via genre co-occurrence pattern in a specific movie. Three index of genre centrality, eigenvector centrality, degree centrality, and bonacich power centrality, were tested for the valued genre network. Results showed that the relationship between genre centrality and movie performance appeared to be inverted U-shaped. This empirical finding is in line with the theory of ambidexterity which emphasizes the balance of exploration and exploitation. In addition, this study can provide practical implications for movie producers, distributors, and theaters that need to develop genre strategies.

The Impact of Influential's Betweenness Centrality on the WOM Effect under the Online Social Networking Service Environment (온라인 소셜 네트워크 서비스 환경에서 유력자의 매개 중심성이 구전 효과에 미치는 영향)

  • Park, Ji Hye;Suh, Bomil
    • Journal of Information Technology Applications and Management
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    • v.20 no.2
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    • pp.127-146
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    • 2013
  • The online social networking services (SNS) have been growing as the means of communication. In this study, we investigated word-of-mouth (WOM) effect under the SNS environment and evaluated the impact of message sender's influence on the WOM effect. Especially, this study focused on the betweenness centrality calculated through the social network analysis (SNA) of SNS network information, and proposed it as the measure of WOM message sender's influence, SNA may provide more accurate and objective measures than subjective self-reporting survey method. Fifty-one Facebook users responded to each of their four Facebook friends, who had been selected based on their betweenness centrality, Statistical analyses were performed using the responses and the betweenness centralities of the Facebook friends. The results showed that the direction (positive vs, negative) of a WOM message in SNS had an impact on the attitude of the message receiver toward the product. Moreover, the betweenness centrality of the message sender as well as his/her opinion leadership had a moderating effect on the WOM effect. Opinion leadership is a measure that has been frequently used for indicating the influence of WOM message sender in the previous studies. Considering the result that the betweenness centrality of the message sender was Significantly correlated to his/her opinion leadership, the betweenness centrality can be used for indicating the influence of WOM message sender.

Social Network Comparison of Netflix, Disney+, and OCN on Twitter Using NodeXL

  • Lee, Soochang;Song, Keuntae;Bae, Woojin;Choi, Joohyung
    • International Journal of Advanced Culture Technology
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    • v.10 no.1
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    • pp.47-54
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    • 2022
  • We analyze and compare the structure of the networks of Netflix, Disney+, and OCN, which are forerunners in OTT market, on Twitter. This study employs NodeXL pro as a visualization software package for social network analysis. As a result of the comparison with values of Vertices, Connected Components, Average Geodesic Distance, Average Betweenness Centrality, and Average Closeness Centrality. Netflix has comparative advantages at Vertices, Connected Components, and Average Closeness Centrality, OCN at Average Geodesic Distance, and Disney+ at Average Betweenness Centrality. Netflix has a more appropriate social network for influencer marketing than Disney+ and OCN. Based on the analysis results, the purpose of this study is to explain the structural differences in the social networks of Netflix, Disney+, and OCN in terms of influencer marketing.

Global Research Trends on Geospatial Information by Keyword Network Analysis (키워드 네트워크 분석을 이용한 지리공간정보의 글로벌 연구 동향 분석)

  • Kim, Byeongsun;Jeong, Minwoo;Jeon, Sangeum;Shin, Dongbin
    • Spatial Information Research
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    • v.23 no.1
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    • pp.69-77
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    • 2015
  • The aim of this study is to examine the research trends of global scientific production of Geospatial Information (GI) papers from 1998 to 2013 by using keyword network analysis. This study constructed keyword network model through papers and keywords related to GI research retrieved from the Web of Science DB and performed keyword network analysis such as Degree Centrality, Betweenness Centrality, and Closeness Centrality. The results show that GI has been steadily applied to various fields, and also the research trends of GI techniques could be quantitatively characterized through keyword network analysis. This study result can be applied to establish the policies and the national R&D planning of geospatial information.