<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Exploration of the structural balance of social networks is of great importance for theoretical analysis and practical use. This study modeled the structural balance of social networks as a mathematical optimization problem by using swarm intelligence, and an efficient discrete particle swarm optimization algorithm was proposed to solve the modeled optimization problem. To take advantage of the topologies of social networks in the algorithm design, the discrete representation of the particle was redefined, and the discrete particle update principles were redesigned. To validate the efficiency of the proposed algorithm, experiments were conducted using synthetic and real-world social networks. The experiments demonstrate that the proposed algorithm not only achieves a balanced social network structure, but also automatically detects the community topology of networks.</p></abstract>

Exploration of the structural balance of social networks is of great importance for theoretical analysis and practical use. This study modeled the structural balance of social networks as a mathematical optimization problem by using swarm intelligence, and an efficient discrete particle swarm optimization algorithm was proposed to solve the modeled optimization problem. To take advantage of the topologies of social networks in the algorithm design, the discrete representation of the particle was redefined, and the discrete particle update principles were redesigned. To validate the efficiency of the proposed algorithm, experiments were conducted using synthetic and real-world social networks. The experiments demonstrate that the proposed algorithm not only achieves a balanced social network structure, but also automatically detects the community topology of networks.

A Novel Social Network Structural Balance Based on the Particle Swarm Optimization Algorithm

School of Mechanical and Electrical Engineering, Xi’an University of Architecture and Technology, Xi’an 710055, China

School of Information Engineering, Yulin University, Yulin 719000, China

Cybernetics and Information Technologies

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Exploration of the structural balance of social networks is of great importance for theoretical analysis and practical use. This study modeled the structural...

A Novel Social Network Structural Balance Based on the Particle Swarm Optimization Algorithm

Published Online: Jul 03, 2015

Page range: 23 - 35

DOI: https://doi.org/10.1515/cait-2015-0026

© by Li Zhao Xing

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.