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 :
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