DocumentCode
169242
Title
Covert nodes mining in social networks based on games theory
Author
Atiao Yang ; Yong Tang ; Jiangbin Wang ; Jieming Chen
Author_Institution
Dept. of Comput. Sci., South China Normal Univ., Guangzhou, China
fYear
2014
fDate
21-23 May 2014
Firstpage
541
Lastpage
545
Abstract
The problem of discovering covert nodes in social network has been widely studied because of its tremendous number of applications in determining critical points in social network, such as detecting terrorist, recommending item for possible customer, finding the source of spreading gossip, etc. In this paper, we utilize game theory to solve this problem. Firstly, we propose the model which analyzes game in the influence transmission. Then we obtain each nodes contribution by calculating the nodes earning in game. The feasibility and effectiveness of our method were verified on a simulation dataset and a real dataset.
Keywords
data mining; game theory; social networking (online); covert nodes mining; critical points; games theory; influence transmission; real dataset; simulation dataset; social network; Collaboration; Game theory; Games; Network topology; Peer-to-peer computing; Social network services; Topology; Covert node problem; Dynamic games; Social network; repeated games;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Supported Cooperative Work in Design (CSCWD), Proceedings of the 2014 IEEE 18th International Conference on
Conference_Location
Hsinchu
Type
conf
DOI
10.1109/CSCWD.2014.6846902
Filename
6846902
Link To Document