Research Article
Knowledge Sharing in Social Network Using Game Theory
@INPROCEEDINGS{10.1007/978-3-642-32615-8_53, author={Ping Zhu and Guiyi Wei and Athanasios Vasilakos and Hung-Yu Wei}, title={Knowledge Sharing in Social Network Using Game Theory}, proceedings={Bio-Inspired Models of Network, Information, and Computing Systems. 5th International ICST Conference, BIONETICS 2010, Boston, USA, December 1-3, 2010, Revised Selected Papers}, proceedings_a={BIONETICS}, year={2012}, month={10}, keywords={Social Network Virtual Community Knowledge Sharing Stimulating Game Theory}, doi={10.1007/978-3-642-32615-8_53} }- Ping Zhu
Guiyi Wei
Athanasios Vasilakos
Hung-Yu Wei
Year: 2012
Knowledge Sharing in Social Network Using Game Theory
BIONETICS
Springer
DOI: 10.1007/978-3-642-32615-8_53
Abstract
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 mechanism by combining the finitely repeated game with basic stimulating mechanism together. Theoretical analyzing indicates that, by introducing incomplete information, the 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 mechanism to the multi-person model.
