Multi-agent System for Privacy Protection Through User Emotions in Social Networks

2017 ◽  
pp. 235-245
Author(s):  
G. Aguado ◽  
V. Julian ◽  
A. Garcia-Fornes
Keyword(s):  
Social Networks ◽  
Privacy Protection ◽  
Multi Agent System ◽  
Agent System ◽  
Multi Agent

Hierarchical Social Network Analysis Using a Multi-Agent System

2013 ◽  
Vol 5 (3) ◽  
pp. 14-32
Author(s):  
Lizhu Ma ◽  
Xin Zhang
Keyword(s):  
Social Networks ◽  
Student Performance ◽  
Hierarchical Clustering ◽  
Hierarchical Structure ◽  
School Quality ◽  
Multi Agent System ◽  
Agent System ◽  
Funding Policies ◽  
Multi Agent ◽  
K 12

The quality of K-12 education has been a major concern in the nation for years. School systems, just like many other social networks, appear to have a hierarchical structure. Understanding this structure could be the key to better evaluating student performance and improving school quality. Many studies have been focusing on detecting hierarchical structure by using hierarchical clustering algorithms. The authors design an interaction-based similarity measure to accomplish hierarchical clustering in order to detect hierarchical structures in social networks (e.g. school district networks). This method uses a multi-agent system, for it is based on agent interactions. With the network structure detected, they also built a model, which is based on the MAXQ algorithm, to decompose the funding policy task into subtasks and then evaluate these subtasks by using funding distribution policies from past years and looking for possible relationships between student performances and funding policies. For the experiment, the authors used real school data from Bexar county’s 15 school districts in Texas. The first result shows that their interaction-based method is able to generate meaningful clustering and dendrograms for social networks. Additionally the authors’ policy evaluation model is able to evaluate funding policies from the past three years in Bexar County and conclude that increasing funding does not necessarily have a positive impact on student performance and it is generally not the case that the more is spent, the better.

Colony Evolution in Social Networks Based on Multi-agent System

2009 ◽  
Author(s):  
Jie Ma ◽  
Dongwei Guo ◽  
Kangping Wang ◽  
Miao Liu ◽  
Sha Chen
Keyword(s):  
Social Networks ◽  
Multi Agent System ◽  
Agent System ◽  
Multi Agent

Detecting cyberbullying in social networks using multi-agent system

2014 ◽  
Vol 12 (4) ◽  
pp. 375-388 ◽  
Author(s):  
Vinita Nahar ◽  
Xue Li ◽  
Hao Lan Zhang ◽  
Chaoyi Pang
Keyword(s):  
Social Networks ◽  
Multi Agent System ◽  
Agent System ◽  
Multi Agent
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