• Title/Summary/Keyword: centrality measures

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The Effect of Social Network on Information Sharing in Franchise System (프랜차이즈시스템의 사회연결망 특성이 정보공유에 미치는 영향)

  • Yun, Han-Sung;Bae, Sang-Wook;Noh, Jung-Koo
    • Journal of Distribution Research
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    • v.16 no.2
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    • pp.95-118
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    • 2011
  • The purpose of this study is as follows. First, we investigate empirically the effects of social network properties such as social network density and centrality of a franchisee on its information sharing with various subjects such as the franchisor and other franchisees in the franchise system. Second, we examine exploratively if tie strength between a franchisee and its franchisor plays a moderating role on the relationship between social network properties and information sharing. The study model was established as shown in

    . We gathered 200 data from franchisees in Busan through a questionnaire survey and used 189 data for our purpose. To improve the quality of data, we selected respondents from the franchisees' owners or managers that had contacted often with their franchisor and other franchisees in the franchise system. Our data analysis began with reliability analysis, exploratory and confirmatory factor analysis, on the multi-item measures of social network density, social network centrality, tie strength, information sharing and control variables such as shared goals and ownership to assess the reliability and validity of those measures. The results were shown that the presented values satisfied the general criteria for reliability and validity. We tested our hypotheses using a hierarchical multiple regression analysis in four steps. Model 1 regressed the dependent variable(information sharing) only on control variables(shared goals, ownership). Model 2 added main effect variables(social network density, social network centrality) in Model 1. Model 3 added a moderating variable(tie strength) in Model 2. Finally, Model 4 added interaction terms between the main variables and the moderating variable in Model 3. We used a mean-centering method for the main variables and the moderating variable to minimize the multicollinearity problem due to the interaction terms in Model 4. Two important empirical findings emerge from this study. In other words, the effects of social network properties and tie strength on a franchisee's information sharing depend on subject types such as the franchisor and other franchisees in franchise system. First, social network centrality, tie strength, the interaction between social network density and tie strength and the interaction between social network centrality and tie strength all affect significantly a franchisee's information sharing with its franchisor. By the way, the interaction between social network centrality and tie strength has a negative effect on its information sharing while the interaction of social network density and tie strength has a positive effect on its information sharing. Second, both social network centrality affects significantly and directly a franchisee's information sharing with other franchisees in the franchise system. However, there does not exist the moderating role of tie strength in the second case. Finally, we suggest the implications of our findings and some avenues for future research.

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Comparing Centrality Measures for Analyzing Co-authorhip Networks (공저 네트워크 분석을 위한 중심성 척도 비교 분석)

  • Lee, Jae Yun
    • Proceedings of the Korean Society for Information Management Conference
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    • 2013.08a
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    • pp.27-30
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    • 2013
  • 공동연구 네트워크의 대표적인 사례인 공저 네트워크는 오랫동안 네트워크 분석의 대상으로 다루어져 왔다. 최근에는 가중 네트워크로서 공저 네트워크에 대한 연구가 활발해지면서 연구자의 영향력을 측정하려는 몇 가지 척도가 제안되었다. 이 연구에서는 공저 네트워크에서의 중심성을 측정하기 위해서 사용된 척도인 가중페이지랭크, 공동연구 h-지수와 공동연구 hs-지수, 복합연결정도중심성, c-지수에 대해서 비교 분석해본다.

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Research Trend Analysis of Publications in the Journal of Home Economics Education Association Using Network Text Analysis (네트워크 텍스트 분석을 이용한 한국가정과교육학회지 논문의 연구 동향 분석)

  • Lee, Yoon-Jung;Kim, Eun Jeung;Kim, Ji sun
    • Journal of Korean Home Economics Education Association
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    • v.31 no.4
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    • pp.1-18
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    • 2019
  • The purpose of this study was to analyze the research trend in home economics education using network text analysis method. The 586 research articles published in the Journal of Home Economics Education Association between July, 2003 and December 2018 were examined using Neckinger 4, a social network analysis software. The frequency and centrality measures(degree centrality, closeness centrality, and betweenness centrality) were calculated for the words appeared throughout the whole period, and the centrality analysis and LAD(Latent Dirichlet Allocation) were conducted for the four sub-periods. The results are as follows: first, the most frequently appeared words are parents, culture, unit, health, career, consumption, practicality, etc. The words such as parents and management scored high in degree centrality; parents and male students in closeness centrality; and male students and units in betweenness centrality. Second, when divided into four periods, the words such as education, family, purpose, class, middle school, and school appeared most frequently across the periods; but some words such as 'purpose' (in period 3 and 4), or 'process' (in period 4) were salient only in certain periods. Third, the words with high centrality were consistent regardless of the types of centrality within each period. Fourth, the topic analysis using LAD showed that curriculum, textbook, family healthiness, teaching-learning, evaluation, dietary life, appearance management, and consumption were the topics consistently appeared across all periods. The topics have become diversified and deepened. New topics such as teacher training and safety appeared in later periods, possibly due to the curriculum and national policy changes, and housing as a less represented topic is suggested as an area that needs further research attention. This study has implication in that it allows researchers to identify the major research interests and the trends in research by researchers in home economic education.

The Distinct Impact Dimensions of the Prestige Indices in Author Citation Networks (저자 인용 네트워크에서 명망성 지표의 차별된 영향력 측정기준에 관한 연구)

  • Ahn, Hyerim;Park, Ji-Hong
    • Journal of the Korean Society for information Management
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    • v.33 no.2
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    • pp.61-76
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    • 2016
  • This study aims at proposing three prestige indices-closeness prestige, input domain, and proximity prestige- as useful measures for the impact of a particular node in citation networks. It compares these prestige indices with other impact indices as it is still unknown what dimensions of impact these indices actually measure. The prestige indices enable us to distinguish the most prominent actors in a directed network, similar to the centrality indices in undirected networks. Correlation analysis and principal component analysis were conducted on the author citation network to identify the differentiated implications of the three prestige indices from the existing impact indices. We selected simple citation counting, h-index, PageRank, and the three kinds of centrality indices which assume undirected networks as the existing impact measures for comparison with the three prestige indices. The results indicate that these prestige indices demonstrate distinct impact dimension from the other impact indices. The prestige indices reflect indirect impact while the others direct impact.

A Study on the e-Learning Communities Interaction Under the CSCL by Using Network Mining (컴퓨터지원협동학습 환경 하에서 네트워크 마이닝을 통한 학습자 상호작용연구)

  • Chung, Nam-Ho
    • Journal of Intelligence and Information Systems
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    • v.11 no.2
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    • pp.17-29
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    • 2005
  • The purpose of the study was to explore the potential of the Social Network Analysis as an analytical tool for scientific investigation of learner-learner, or learner-tutor interaction within a Computer Supported Corporative Learning (CSCL) environment. Theoretical and methodological implication of the Social Network Analysis had been discussed. Following theoretical analysis, an exploratory empirical study was conducted to test statistical correlation between traditional performance measures such as achievement and team contribution index, and the centrality measure, one of the many quantitative measures the Social Network Analysis provides. Results indicate the centrality measure was correlated with the higher order teaming performance and the peer-evaluated contribution indices. An interpretation of the results and their implication to instructional design theory and practices were provided along with some suggestions for future research.

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Design and Implementation of the Menu Navigation using Social Network Analysis among the Menus of Management Information System (사회연결망분석을 이용한 경영정보시스템 화면들의 메뉴 네비게이션 설계 및 구현)

  • Lee, Min-Jung;Kim, Jun-Woo
    • Journal of the Korea Society of Computer and Information
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    • v.19 no.9
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    • pp.151-160
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    • 2014
  • Recently enterprises, which posses high-speed internet and high-performance computers, have tried to use MIS(management information systems) to deal with whole task efficiently. This study considers design of menu navigation using SNA(social network analysis) to be able to move between menus of MIS efficiently. We extracted the important menu lists through the high SNA measures such as degree centrality, betweenness centrality and closeness centrality, developed web-pages and investigated its application. The findings will be used for design of web menu navigation and guide of strategic planning for MIS.

Visual Observation Confidence based GMM Face Recognition robust to Illumination Impact in a Real-world Database

  • TRA, Anh Tuan;KIM, Jin Young;CHAUDHRY, Asmatullah;PHAM, The Bao;Kim, Hyoung-Gook
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.4
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    • pp.1824-1845
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    • 2016
  • The GMM is a conventional approach which has been recently applied in many face recognition studies. However, the question about how to deal with illumination changes while ensuring high performance is still a challenge, especially with real-world databases. In this paper, we propose a Visual Observation Confidence (VOC) measure for robust face recognition for illumination changes. Our VOC value is a combined confidence value of three measurements: Flatness Measure (FM), Centrality Measure (CM), and Illumination Normality Measure (IM). While FM measures the discrimination ability of one face, IM represents the degree of illumination impact on that face. In addition, we introduce CM as a centrality measure to help FM to reduce some of the errors from unnecessary areas such as the hair, neck or background. The VOC then accompanies the feature vectors in the EM process to estimate the optimal models by modified-GMM training. In the experiments, we introduce a real-world database, called KoFace, besides applying some public databases such as the Yale and the ORL database. The KoFace database is composed of 106 face subjects under diverse illumination effects including shadows and highlights. The results show that our proposed approach gives a higher Face Recognition Rate (FRR) than the GMM baseline for indoor and outdoor datasets in the real-world KoFace database (94% and 85%, respectively) and in ORL, Yale databases (97% and 100% respectively).

A Comparison of Hospice Care Research Topics between Korea and Other Countries Using Text Network Analysis (텍스트네트워크분석을 활용한 국내·외 호스피스 간호 연구 주제의 비교 분석)

  • Park, Eun-Jun;Kim, Youngji;Park, Chan Sook
    • Journal of Korean Academy of Nursing
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    • v.47 no.5
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    • pp.600-612
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    • 2017
  • Purpose: This study aimed to identify and compare hospice care research topics between Korean and international nursing studies using text network analysis. Methods: The study was conducted in four steps: 1) collecting abstracts of relevant journal articles, 2) extracting and cleaning keywords (semantic morphemes) from the abstracts, 3) developing co-occurrence matrices and text-networks of keywords, and 4) analyzing network-related measures including degree centrality, closeness centrality, betweenness centrality, and clustering using the NetMiner program. Abstracts from 347 Korean and 1,926 international studies for the period of 1998-2016 were analyzed. Results: Between Korean and international studies, six of the most important core keywords-"hospice," "patient," "death," "RNs," "care," and "family"-were common, whereas "cancer" from Korean studies and "palliative care" from international studies ranked more highly. Keywords such as "attitude," "spirituality," "life," "effect," and "meaning" for Korean studies and "communication," "treatment," "USA," and "doctor" for international studies uniquely emerged as core keywords in recent studies (2011~2016). Five subtopic groups each were identified from Korean and international studies. Two common subtopics were "hospice palliative care and volunteers" and "cancer patients." Conclusion: For a better quality of hospice care in Korea, it is recommended that nursing researchers focus on study topics of patients with non-cancer disease, children and family, communication, and pain and symptom management.

Exploring the Influence of Vehicle Mobility on Information Spreading in VANETs

  • Li, Zhigang;Wang, Xin;Yue, Xinan;Ji, Yingli;Wang, Hua
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.2
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    • pp.800-813
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    • 2021
  • With the advent of 5G communications, internet of vehicles technology has been widely used in vehicles. Then the dynamic spread of information between vehicles began to come into focus with more research. It is well known that the identification of nodes with great spread influence has always been a hot topic in the field of information spreading. Most of the existing work measures the propagation influence by degree centrality, betweenness centrality and closeness centrality. In this paper, we will identify influential vehicle nodes based on the mobility characteristics of vehicles to explore the information spreading between vehicles in VANETs. Different from the above methods, we mainly explore the influence of the radius of gyration and vehicle kilometers of travel on information spreading. We use a real vehicle trajectory data to simulate the information transmission process between vehicles based on the susceptible-infected-recovered SIR model. The experimental results show that the influence of information spreading does not enhance with increasing radius of gyration and vehicle kilometers of travel. The fact is that both the radius of gyration and the distance travelled have a significant influence on information spreading when they are close to the median. When the value of both is large or small, it has little influence on information spreading. In view of this results, we can use the radius of gyration and vehicle kilometers of travel to better facilitate the transmission of information between vehicles.

Ascertaining the Structure and Content of a National Scholarly Web Space Based on Content Analysis (내용 분석을 통한 한국의 학술적 웹 공간 구조 분석)

  • Chung, Young-Mee;Yu, So-Young
    • Journal of the Korean Society for information Management
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    • v.26 no.3
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    • pp.7-24
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    • 2009
  • Since the Web is dynamic, it is necessary to analyze scholarly Web space with both quantitative and qualitative methods for better understanding of communication characteristics. In this study, we analyzed contents of pages and links to ascertain the characteristics of Korean scholarly Web space in terms of network structure and communication behavior. The result shows that the structure of the original network with all the external links remained is not much different from that of the network with activated external links only. However, the purposes of linking vary among scholarly institutions. The centrality measures correlate more strongly with the clustering coefficient than with the constraint index implying the similar explanatory power of the two types of structural indices.