Knowledge Sharing in Social Network Using Game Theory

Stimulating is an important mechanism in Virtual Community (VC) during the Knowledge Sharing (KS) process. In this paper, we combine the power of game theory and stimulating mechanism together to optimize the KS process in Social Network (SN). We first model the basic stimulating mechanism as a static game of complete information, under which the stimulating threshold for Nash Equilibrium (NE) is derived. Next, we modify the static model by introducing the KREPS-MILGROM-ROBERTS-WILSON (KMRW) reputation model, where the dynamic case is studied and the Perfect Bayesian Equilibrium is proved. We then propose a novel rational stimulating mechanism by combining the finitely repeated game with basic stimulating mechanism together. Theoretical analyzing indicates that, by introducing incomplete information, the rational stimulating achieves a lower cost; through stimulating, the Perfect Bayesian Equilibrium’s condition is satisfied and the KS rate will approach 100% as long as the KS process is repeated enough. Finally, we extend our rational stimulating mechanism to the multi-person model.

[1]  E. Churchill,et al.  Social Networks and Social Networking , 2005 .

[2]  K. J. R. Liu,et al.  Cooperation Stimulation Strategies for Peer-To-Peer Wireless Video Streaming Social Networks , 2010 .

[3]  Robert Gibbons,et al.  A primer in game theory , 1992 .

[4]  Mary Beth Rosson,et al.  Notification and awareness: synchronizing task-oriented collaborative activity , 2003, Int. J. Hum. Comput. Stud..

[5]  Masanori Sugimoto,et al.  Beyond binary choices: Integrating individual and social creativity , 2005, Int. J. Hum. Comput. Stud..

[6]  M. Dufwenberg.  Game theory. , 2011, Wiley interdisciplinary reviews. Cognitive science.

[7]  George C. Polyzos,et al.  Efficient cooperative searching on the Web: system design and evaluation , 2004, Int. J. Hum. Comput. Stud..

[8]  野中 郁次郎,et al.  The Knowledge-Creating Company: How , 1995 .

[9]  W. S. Chow,et al.  Social network, social trust and shared goals in organizational knowledge sharing , 2008, Inf. Manag..

[10]  D. Hindman.  The Virtual Community: Homesteading on the Electronic Frontier , 1996 .

[11]  David M. Kreps,et al.  Rational cooperation in the finitely repeated prisoners' dilemma , 1982 .

[12]  Christine Halverson,et al.  Guest Editors' Introduction: Social Networks and Social Networking , 2005, IEEE Internet Comput..

[13]  Gail E. Kaiser,et al.  genSpace: Exploring social networking metaphors for knowledge sharing and scientific collaborative work , 2008, 2008 23rd IEEE/ACM International Conference on Automated Software Engineering - Workshops.

[14]  Yufei Yuan,et al.  Agent-based buddy-finding methodology for knowledge sharing , 2006, Inf. Manag..

[15]  Yianni Attikiouzel,et al.  Responses to Elkan (Christopher J.S. de Silva, Yanni Attikiouzel) , 1994, IEEE Expert.

[16]  Stephen J. H. Yang,et al.  A social network-based system for supporting interactive collaboration in knowledge sharing over peer-to-peer network , 2008, Int. J. Hum. Comput. Stud..

[17]  J.D. Wang,et al.  Mutual choices of knowledge sharing in social networks , 2004, 2004 IEEE International Engineering Management Conference (IEEE Cat. No.04CH37574).