• Title/Summary/Keyword: Social network centrality

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The effects of the organizational characteristics and interorganizational network level on social welfare organizations' effectiveness -Focused on resource capability of women's welfare organization- (사회복지조직의 특성과 네트워크 수준이 조직효과성에 미치는 영향 -여성복지조직의 자원확보능력을 중심으로-)

  • Jang, Yeon Jin
    • Korean Journal of Social Welfare Studies
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    • v.44 no.3
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    • pp.147-175
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    • 2013
  • The purpose of this study is to examine the effects of the organizational characteristics and interorganizational network level on social welfare organizationas' effectiveness using structural equation model. For achieving this purpose, this study defined organizational effectiveness as financial, human and physical resource capability according to resource systems approach. Organizational characteristics variables included the number of qualified staff, degree of resource dependency, the proportion of government subsidies, the main organizational philosophy, establishment year, the attitude of top manager and the number of informal ties. Interorganizational network variables were divided by outdegree centrality and indegree centrality. The data collected from women's welfare organizations in Seoul through survey method. The analysis tools used the UCINET 6.245 for the network analysis and AMOS 18.0 for the structural equation model. The results of this study are as follows. The factors affected on the financial resource capacity were the number of qualified staff, the proportion of government subsides and the indegree centrality. Meanwhile, only indegree centrality directly influenced on the human resource capability. The significant affecting factors on physical resource capacity were the number of qualified staff, the attitude of top manager and informal ties. Based on these results, the implications of this study and the ways to enhance social welfare organization's effectiveness were discussed.

Analysis of Network for Asian Cup Soccer Final based on Social Network Theory: Based on Centrality Indexes (사회 연결망 이론에 근거한 아시안컵 축구 결승전 네트워크 분석: 중심성 지표를 중심으로)

  • Kim, Sun-Duck;Seong, Tae-Young;Lee, Dong-Min;Lee, Man-Hyung
    • The Journal of the Korea Contents Association
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    • v.16 no.5
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    • pp.205-216
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    • 2016
  • This study aimed to discover the most influential player in the network of Soccer game and how individual players contribute within the team with quantitative capabilities they possess. It also examined whether or not the network of relationship between players and the coach's tactics were in harmony. The results showed high level of correlation between the network between offenders and defenders according to tactics of the coach during the first half. It can be said that each players fulfilled their role and formed a network within them to lead the game and form a virtuous network structure. On the other hand, the overall network of the team was focused on a specific player during the second half. But the coach's appropriate use of substitutes and change in tactics stabilized the network balance between the players.

The Empirical Study on the Effect of Technology Exchanges in the Fourth Industrial Revolution between Korea and China: Focused on the Firm Social Network Analysis (한중 4차산업혁명 기술교류 및 효과에 대한 실증연구: 기업 소셜 네트워크 분석 중심으로)

  • Zhou, Zhenxin;Sohn, Kwonsang;Hwang, Yoon Min;Kwon, Ohbyung
    • The Journal of Society for e-Business Studies
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    • v.25 no.3
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    • pp.41-61
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    • 2020
  • China's rapid development and commercialization of high-tech technologies in the fourth industrial revolution has led to effective technology exchanges between Korean and Chinese firms becoming more important to Korea's mid-term and long-term industrial development. However, there is still a lack of empirical research on how technology exchanges between Korean and Chinese firms proceed and their effectiveness. In response, this study conducted a social network analysis based on text mining data of Korea-China business technology exchange and cooperation articles introduced in the news from 2018 to March 2020 on the current status and effects of Korea-China technology exchanges related to the fourth industrial revolution, and conducted a regression analysis how network centrality effect on the firm performance. According to the results, most of the Korean major electronic firms are actively networking with Chinese firms and institutions, showing high centrality in the centrality index. Korean telecommunication firms showed high betweenness centrality and subgraph centrality, and Korean Internet service providers and broadcasting contents firms showed high eigenvector centrality. In addition, Chinese firms showed higher betweenness centrality than Korean firms, and Chinese service firms showed higher closeness centrality than manufacturing firms. As a result of regression analysis, this network centrality had a positive effect on firm performance. To the best of our knowledge, this is the first to analyze the impact of the technical cooperation between Korean and Chinese firms under the fourth industrial revolution context. This study has theoretical implications that suggested the direction of social network analysis-based empirical research in global firm cooperation. Also, this study has practical implications that the guidelines for network analysis in setting the direction of technical cooperation between Korea and China by firms or governments.

Characterizing the Structure of China's Passenger Railway Network Based on the Social Network Analysis(SNA) Approaches : Focused on the 2008, 2013, and 2018 Railway Service Data, Respectively (사회 네트워크 분석 방법론에 기초한 중국의 여객 철도 네트워크 특성 분석 : 2008년, 2013년, 2018년 운행 데이터를 중심으로)

  • Zhao, Pei-Song;Lee, Jin-Hee;Lee, Man-Hyung
    • The Journal of the Korea Contents Association
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    • v.19 no.10
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    • pp.685-697
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    • 2019
  • The study aimed to analyze the structure of China's passenger railway network in the years of 2008, 2013, and 2018, respectively. At the same time, it tried to investigate its derivative impact on the patterns of Chinese urban network. The analytical tool was based on the NetMiner4.0. In order to measure network characteristics of China's passenger railway network, it primarily focused on the degree centrality, betweenness centrality, and closeness centrality. First of all, the higher degree centralities, with a few exceptions, were observed in BeiJing, ShangHai, GuangZhou, WuHan, XiAn, ChengDu, HaErBin, and ShenYang over a decade. In contrast, the higher betweenness centralities were recorded in cities of higher development potential including WuLuMuQi, GuiYang, ShenYang, and KunMing. The closeness centrality analyses confirmed the fact that most metropoles like BeiJing, ShangHai, and GuangZhou kept the highest train accessibility during the same research period. At the same time, the opening up of a new stretch of high speed railway network has consecutively strengthened connectivity between BeiJing and TianJin. Owing to unprecedented development of railway traffic and its extensive operations, this study believes that Chinese major cities, without interruption, would pursue a series of urban policy alternatives geared towards railway stations-oriented networking and competitively try to extend their network ranges.

Social Network Analysis of Shared Bicycle Usage Pattern Based on Urban Characteristics: A Case Study of Seoul Data (도시특성에 기반한 공유 자전거 이용 패턴의 소셜 네트워크 분석 연구: 서울시 데이터 사례 분석)

  • Byung Hyun Lee;Il Young Choi;Jae Kyeong Kim
    • 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.

Investigating the Behavior of College Students in Class Registration using Social Network Analysis (사회 네크워크 분석으로 본 수강신청 행태)

  • Lim, Sung-Min;Kim, Jinheum
    • The Korean Journal of Applied Statistics
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    • v.26 no.4
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    • pp.661-674
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    • 2013
  • We investigate the class registration behavior of college students with data collected from the spring semester of 2012. The network originally consists of a 2-mode network between a student and class subjects. We first transform the 2-mode network into 1-mode network of students. We also subdivide it into a smaller network such as components and communities to understand the detailed behavior of students in class registration. Finally, the relationship between GPA and the centrality measures, gender, and grade of students is analyzed using a multiple regression analysis.

Analysis of Regional Centrality by Investigating Direct and Indirect Flows of Commuters (통근통행에 의한 직·간접 흐름을 이용한 지역의 중심성 분석)

  • Lee, Jong-Sang;Seo, Ducksu
    • Journal of Agricultural Extension & Community Development
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    • v.27 no.3
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    • pp.125-134
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    • 2020
  • The regional centrality plays a very important role in national and regional planning and it is measured by data such as people, goods, and information flows among regions. The inter-regional flows are usually considered by only direct flows, yet indirect flows, which are generated accordingly from direct flows, are not critically considered. Most centrality studies have also hardly reflected the indirect flow in the network analysis. This study demonstrates the significance of the indirect flows to enhance accuracy of the regional centrality. The nationwide dataset of inter-regional commuter traffic matrix is used in this study and analysed into two groups; one to consider only direct flow and the other both direct and indirect flows. The results indicate remarkable differences of centrality raking between two groups such as Yeongam of Jeonnam Province(+60th), Eumseong of Chungbuk Province(+57th), Gwacheon of Gyeonggi Province (-35th), and Nowon of Seoul (-32nd). It clearly shows the significant influence of indirect flow for regional centrality study. This also reveals regional centrality ranking in Korea by considering direct and indirect flows of commuters. Jung, Gangnam, and Jongno of Seoul are categorized in the highest rank group and Ulleung of Gyeongbuk, Ongjin of Incheon, and Jindo of Jeonnam are in the lowest group. The top group includes seven districts of Seoul, two of Busan, and one of Gyeonggi Province. The bottom group includes mostly island and costal areas. As this study shows an accurate method of centrality measurement, it has a significant implication to lead an effective regional planning.

Structural Properties of Social Network and Diffusion of Product WOM: A Sociocultural Approach (사회적 네트워크 구조특성과 제품구전의 확산: 사회문화적 접근)

  • Yoon, Sung-Joon;Han, Hee-Eun
    • Journal of Distribution Research
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    • v.16 no.1
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    • pp.141-177
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    • 2011
  • I. Research Objectives: Most of the previous studies on diffusion have concentrated on efficacy of WOM communication with the use of variables at individual level (Iacobucci 1996; Midgley et al. 1992). However, there is a paucity of studies which investigated network's structural properties as antecedents of WOM from the perspective of consumers' sociocultural propensities. Against this research backbone, this study attempted to link the network's structural properties and consumer' WOM behavior on cross-national basis. The major research objective of this study was to examine the relationship between network properties and WOM by comparing Korean and Chinese consumers. Specific objectives of this research are threefold; firstly, it sought to examine whether network properties (i.e., tie strength, centrality, range) affect WOM (WOM intention and quality of WOM). Secondly, it aimed to explore the moderating effects of cutural orientation (uncertainty avoidance and individuality) on the relationship between network properties and WOM. Thirdly, it substantiates the role of innovativeness as antecedents to both network properties and WOM. II. Research Hypotheses: Based on the above research objectives, the study put forth the following research hypotheses to validate. ${\cdot}$ H 1-1 : The Strength of tie between two counterparts within network will positively influence WOM effectivenes ${\cdot}$ H 1-2 : The network centrality will positively influence the WOM effectiveness ${\cdot}$ H 1-3 : The network range will positively influence the WOM effectiveness ${\cdot}$ H 2-1 : The consumer's uncertainty avoidance tendency will moderate the relationship between network properties and WOM effectiveness ${\cdot}$ H 2-2 : The consumer's individualism tendency will moderate the relationship between network properties and WOM effectiveness ${\cdot}$ H 3-1 : The consumer's innovativeness will positively influence the social network properties ${\cdot}$ H 3-2 : The consumer's innovativeness will positively influence WOM effectiveness III. Methodology: Through a pilot study and back-translation, two versions of questionnaire were prepared, one in Korean and the other in Chinese. The chinese data were collected from the chinese students enrolled in language schools in Suwon city in Korea, while Korean data were collected from students taking classes in a major university in Seoul. A total of 277 questionnaire were used for analysis of Korean data and 212 for Chinese data. The reason why Chinese students living in Korea rather than in China were selected was based on two factors: one was to neutralize the differences (ie, retail channel availability) that may arise from living in separate countries and the second was to minimize the difference in communication venues such as internet accessibility and cell phone usability. SPSS 12.0 and AMOS 7.0 were used for analysis. IV. Results: Prior to hypothesis verification, mean differences between the two countries in terms of major constructs were performed with the following result; As for network properties (tie strength, centrality and range), Koreans showed higher scores in all three constructs. For cultural orientation traits, Koreans scored higher only on uncertainty avoidance trait than Chinese. As a result of verifying the first research objective, confirming the relationship between network properties and WOM effectiveness, on Korean side, tie strength(Beta=.116; t=1.785) and centrality (Beta=.499; t=6.776) significantly influenced on WOM intention, and similar finding was obtained for Chinese side, with tie strength (Beta=.246; t=3.544) and centrality (Beta=.247; t=3.538) being significant. However, with regard to WOM argument quality, Korean data yielded only centrality (Beta=.82; t=7.600) having a significant impact on WOM, whereas China showed both tie strength(Beat=.142; t=2.052) and centrality(Beta=.348; t=5.031) being influential. To answer for the second research objective addressing the moderating role of cultural orientation, moderated regression anaylsis was performed and the result showed that uncertainty avoidance moderated between network range and WOM intention for both Korea and China, But for Korea, the uncertainty avoidance moderated between tie strength and WOM quality, while for China it moderated between network range and WOM intention. And innovativeness moderated between tie strength and WOM intention for Korea but it moderated between network range and WOM intention for China. As a result of analysing for third research objective, we found that for Korea, innovativeness positively influenced centrality only (Beta=.546; t=10.808), while for China it influenced both tie strength (Beta=.203; t=2.998) and centrality(Beta=.518; t=8.782). But for both countries alike, the innovativeness influenced positively on WOM (WOM intention and WOM quality). V. Implications: The study yields the two practical implications. Firstly, the result suggests that companies targeting multinational customers need to identify segments which are susceptible to the positive WOM and WOM information based on individual traits such as uncertainty avoidance and individualism and based on that, develop marketing communication strategy. Secondly, the companies need to divide the market on Roger's five innovation stages and based on this information, enforce marketing strategy which utilizes social networking tools such as public media and WOM. For instance, innovator and early adopters, if provided with new product information, will be able to capitalize upon the network advantages and thus add informational value to network operations using SNS or corporate blog.

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Social Network Analysis and Its Applications for Authors and Keywords in the JKSS

  • Kim, Jong-Goen;Choi, Soon-Kuek;Choi, Yong-Seok
    • Communications for Statistical Applications and Methods
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    • v.19 no.4
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    • pp.547-558
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    • 2012
  • Social network analysis is a graphical technique to search the relationships and characteristics of nodes (people, companies, and organizations) and an important node for positioning a visualized social network figure; however, it is difficult to characterize nodes in a social network figure. Therefore, their relationships and characteristics could be presented through an application of correspondence analysis to an affiliation matrix that is a type of similarity matrix between nodes. In this study, we provide the relationships and characteristics around authors and keywords in the JKSS(Journal of the Korean Statistical Society) of the Korean Statistical Society through the use of social network analysis and correspondence analysis.

Study of Virtual Goods Purchase Model Applying Dynamic Social Network Structure Variables (동적 소셜네트워크 구조 변수를 적용한 가상 재화 구매 모형 연구)

  • Lee, Hee-Tae;Bae, Jungho
    • Journal of Distribution Science
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    • v.17 no.3
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    • pp.85-95
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    • 2019
  • Purpose - The existing marketing studies using Social Network Analysis have assumed that network structure variables are time-invariant. However, a node's network position can fluctuate considerably over time and the node's network structure can be changed dynamically. Hence, if such a dynamic structural network characteristics are not specified for virtual goods purchase model, estimated parameters can be biased. In this paper, by comparing a time-invariant network structure specification model(base model) and time-varying network specification model(proposed model), the authors intend to prove whether the proposed model is superior to the base model. In addition, the authors also intend to investigate whether coefficients of network structure variables are random over time. Research design, data, and methodology - The data of this study are obtained from a Korean social network provider. The authors construct a monthly panel data by calculating the raw data. To fit the panel data, the authors derive random effects panel tobit model and multi-level mixed effects model. Results - First, the proposed model is better than that of the base model in terms of performance. Second, except for constraint, multi-level mixed effects models with random coefficient of every network structure variable(in-degree, out-degree, in-closeness centrality, out-closeness centrality, clustering coefficient) perform better than not random coefficient specification model. Conclusion - The size and importance of virtual goods market has been dramatically increasing. Notwithstanding such a strategic importance of virtual goods, there is little research on social influential factors which impact the intention of virtual good purchase. Even studies which investigated social influence factors have assumed that social network structure variables are time-invariant. However, the authors show that network structure variables are time-variant and coefficients of network structure variables are random over time. Thus, virtual goods purchase model with dynamic network structure variables performs better than that with static network structure model. Hence, if marketing practitioners intend to use social influences to sell virtual goods in social media, they had better consider time-varying social influences of network members. In addition, this study can be also differentiated from other related researches using survey data in that this study deals with actual field data.