Improvement of the Recognition of Relationships in Social Networks Using Complementary Graph Coloring Based on Cellular Automata

2019 ◽  
Author(s):  
Mostafa Kashani ◽  
Saeid Gorgin ◽  
Seyed Vahab Shojaedini
Keyword(s):  
Social Networks ◽  
Cellular Automata ◽  
Graph Coloring ◽  
Complementary Graph

Graph coloring and ACO based summarization for social networks

2017 ◽  
Vol 74 ◽  
pp. 115-126 ◽  
Author(s):  
Mohamed Atef Mosa ◽  
Alaa Hamouda ◽  
Mahmoud Marei
Keyword(s):  
Social Networks ◽  
Graph Coloring

scholarly journals The Spreading of Information in Online Social Networks through Cellular Automata

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Yuda Wang ◽  
Gang Li
Keyword(s):  
Social Networks ◽  
Cellular Automata ◽  
Infection Rate ◽  
Online Social Networks ◽  
Information Dissemination ◽  
Epidemic Models ◽  
Computational Method ◽  
Online Information ◽  
Information Dynamics ◽  
Information Spreading

Epidemic dynamics in complex networks have been extensively studied. Due to the similarity between information and disease spreading, most studies on information dynamics use epidemic models and merely consider the characteristics of online social networks and individual’s cognitive. In this paper, we propose an online social networks information spreading (OSIS) model combining epidemic models and individual’s cognitive psychology. Then we design a cellular automata (CA) method to provide a computational method for OSIS. Finally, we use OSIS and CA to simulate the spreading and evolution of information in online social networks. The experimental results indicate that OSIS is effective. Firstly, individual’s cognition affects online information spreading. When infection rate is low, it prevents the spreading, whereas when infection rate is sufficiently high, it promotes transmission. Secondly, the explosion of online social network scale and the convenience of we-media greatly increase the ability of information dissemination. Lastly, the demise of information is affected by both time and heat decay rather than probability. We believe that these findings are in the right direction for perceiving information spreading in online social networks and useful for public management policymakers seeking to design efficient programs.

scholarly journals Improving Friends Matching in Social Networks Using Graph Coloring

2016 ◽  
Vol 15 (8) ◽  
pp. 7028-7034 ◽  
Author(s):  
Omayya Murad ◽  
Azzam Sleit ◽  
Ahmad Sharaiah
Keyword(s):  
Social Networks ◽  
Graph Coloring ◽  
Time Complexity ◽  
Linear Time ◽  
Family Members ◽  
General Information ◽  
Home Town

Recently, most of people have their own profiles in different social networks. Usually, their profiles have some brief description about their personnel picture, family members, home town, career, date of birth etc. which indicate other people know some general information about others. In social networks, usually friends recommendation is done by finding the most mutual friends and suggest them to be friends. In this paper, we will introduce an algorithm, with a linear time complexity, that helps people to get not only good friends but also  have same characteristics. 

Multilayer Social Networks

2016 ◽  
Author(s):  
Mark E. Dickison ◽  
Matteo Magnani ◽  
Luca Rossi
Keyword(s):  
Social Networks ◽  
Multilayer Social Networks
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