Multi-layer network community detection model based on attributes and social interaction intensity

2019 ◽  
Vol 77 ◽  
pp. 300-313 ◽  
Author(s):  
Xiaoming Li ◽  
Guagquan Xu ◽  
Litao Jiao ◽  
Yinan Zhou ◽  
Wei Yu
Keyword(s):  
Social Interaction ◽  
Community Detection ◽  
Detection Model ◽  
Network Community ◽  
Model Based ◽  
Interaction Intensity

Ensemble method: Community detection based on game theory

2014 ◽  
Vol 28 (30) ◽  
pp. 1450211 ◽  
Author(s):  
Xia Zhang ◽  
Zhengyou Xia ◽  
Shengwu Xu ◽  
J. D. Wang
Keyword(s):  
Game Theory ◽  
Social Network ◽  
Community Detection ◽  
Online Social Network ◽  
Cost Effective ◽  
Detection Algorithm ◽  
Research Area ◽  
Detection Model ◽  
Model Based ◽  
Active Research

Timely and cost-effective analytics over social network has emerged as a key ingredient for success in many businesses and government endeavors. Community detection is an active research area of relevance to analyze online social network. The problem of selecting a particular community detection algorithm is crucial if the aim is to unveil the community structure of a network. The choice of a given methodology could affect the outcome of the experiments because different algorithms have different advantages and depend on tuning specific parameters. In this paper, we propose a community division model based on the notion of game theory, which can combine advantages of previous algorithms effectively to get a better community classification result. By making experiments on some standard dataset, it verifies that our community detection model based on game theory is valid and better.

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