Title :
A particle swarm optimization approach for handling network social balance problem
Author :
Cai, Qing ; Gong, Maoguo ; Ma, Lijia ; Wang, Shanfeng ; Jiao, Licheng ; Du, Haifeng
Author_Institution :
Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, International Research Center for Intelligent Perception and Computation, Xidian University, Xi´an, Shaanxi Province 710071, China
Abstract :
Social balance property is an eminent feature of social networks. Many creative efforts concerning social balance have been done. This paper presents an optimization idea to solve the social balance of complex social networks. A single objective optimization model integrating the network balance and the community properties is proposed towards the social balance problem. A discrete particle swarm optimization algorithm is introduced to solve the proposed optimization model. Extensive experiments on synthetic and real-world signed networks demonstrate that the proposed model does make sense and the introduced optimization algorithm is promissing for solving the social balance problem.
Keywords :
Biological system modeling; Computational modeling; Indexes; Optimization; Particle swarm optimization; Social network services; Tin; community structure; evolutionary computation; particle swarm optimization; signed network; social balance;
Conference_Titel :
Evolutionary Computation (CEC), 2015 IEEE Congress on
Conference_Location :
Sendai, Japan
DOI :
10.1109/CEC.2015.7257287