SNS 구성원 간 신뢰망 구조 분석방법 = A Method to Analyze the Structure of Interpersonal Trust Network in SNS

다국어 초록 (Multilingual Abstract)

Many studies have pointed out that trust is the most important component of social capital. Although there have been lots of attempts to measure level of trust between members of community, it is hard to find studies which examine trust from the standpoint of structural aspects. Because of the recent rapid growth of SNS and openness trend on members and their friendship information, it became possible to understand the structure of trust relationships among users in SNS. This study aims to facilitate interpersonal trust by comparing the structure of the trust network among social network users. For this purpose, it proposes a method to explore the structure of trust network and strategies to evolve toward more open structure. In experiments to distinguish structure of trust network with three social network communities, it is discovered that ADVOGATO has characteristics of open and collective network together whereas EPINION and FILMTRUST have collective and open characteristics respectively.

목차 (Table of Contents)

• Abstract
• 1. 서론
• 2. 신뢰망 구조에 대한 기존연구
• 3. 신뢰망 구조의 파악 방법
• 4. 사례연구
• 5. 결론 및 시사점
• References

참고문헌 (Reference)

1 Yamagishi, T., "Uncertainty, trust and commitment formation in the United States and Japan" 104 (104): 165-194, 1998

2 Fukuyama, F., "Trust : The social virtues and the creation of prosperity" The Free Press 1995

3 Putnam, R. D., "The prosperous community :Social capital and public affairs" The American Prospect 35-42, 1993

4 Yamagishi, T., "Significance and the structure of trust : Theoretical and empirical research on trust and commitment relations" 2 : 1-59, 1995

5 Martin, S., "OpenOrd : an open-source toolbox for large graph layout" The International Society For Optical Engineering 2011

6 Latapy, M., "Main-memory Triangle Computations for Very Large(Sparse(Power-Law))Graphs" 407 (407): 458-473, 2008

7 Fruchterman, T. M. J., "Graph drawing by force-directed placement" 21 (21): 1129-1164, 1991

8 Granovetter, M., "Getting a job : A study of contacts and careers" Harvard University Press 1974

9 Clauset, A., "Finding community structure in very large networks" E70 : 2004

10 Wu, F., "Finding communities in linear time : a physics approach" 38 (38): 331-338, 2004

11 Newman, M. E. J., "Finding and evaluating community structure in networks" E69 : 2004

12 Blondel, V. D., "Fast unfolding of communities in large networks" 10 : 2008

13 Tarjan, R., "Depth-First Search and Linear Graph Algorithms" 1 (1): 146-160, 1972

14 Radicchi, F., "Defining and identifying communities in networks" 101 (101): 2658-2663, 2004

15 Pons, P., "Computing Communities in Large Networks Using Random Walks" 10 : 191-218, 2006

16 Newman, M. E. J., "Analysis of weighted networks" E70 : 2004

17 Brandes, U., "A Faster Algorithm for Betweenness Centrality" 25 (25): 163-177, 2001