Crash of social networks with cherished connections : a simulation study
No matter the level of engagement from community to global platforms, every living organisms have some role in a social network. When combined, these species interact with each other, creating a complex network. As we understand it, all our actions may affect others. There have been extensive effort...
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2021
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sg-ntu-dr.10356-1491052023-07-07T17:40:27Z Crash of social networks with cherished connections : a simulation study Nur Diana Zainuren XIAO Gaoxi School of Electrical and Electronic Engineering EGXXiao@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Simulation and modeling No matter the level of engagement from community to global platforms, every living organisms have some role in a social network. When combined, these species interact with each other, creating a complex network. As we understand it, all our actions may affect others. There have been extensive efforts done in researching the understanding of the growth and evolution of these networks. However, understanding the phenomenon of systems crashing is still suffering from a lack of research and remains unexplored for many years. The crash of social networks can be viewed as unpredictable. A model called the ‘K-Q Cascade’ is introduced to simulate the outcome of survivability of different social networks. The main aspect focuses on the Erdös−Rényi network, Scale Free network, and Exponential network. On top of looking at the K-Q Cascade model, we will investigate the effects of cherished connections in a social network. Simulation will be done over a few test scenarios to observe how a network reacts. Bachelor of Engineering (Electrical and Electronic Engineering) 2021-05-26T13:06:48Z 2021-05-26T13:06:48Z 2021 Final Year Project (FYP) Nur Diana Zainuren (2021). Crash of social networks with cherished connections : a simulation study. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/149105 https://hdl.handle.net/10356/149105 en application/pdf Nanyang Technological University |
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Engineering::Computer science and engineering::Computing methodologies::Simulation and modeling Nur Diana Zainuren Crash of social networks with cherished connections : a simulation study |
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No matter the level of engagement from community to global platforms, every living organisms have some role in a social network. When combined, these species interact with each other, creating a complex network. As we understand it, all our actions may affect others. There have been extensive efforts done in researching the understanding of the growth and evolution of these networks. However, understanding the phenomenon of systems crashing is still suffering from a lack of research and remains unexplored for many years. The crash of social networks can be viewed as unpredictable.
A model called the ‘K-Q Cascade’ is introduced to simulate the outcome of survivability of different social networks. The main aspect focuses on the Erdös−Rényi network, Scale Free network, and Exponential network. On top of looking at the K-Q Cascade model, we will investigate the effects of cherished connections in a social network. Simulation will be done over a few test scenarios to observe how a network reacts. |
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XIAO Gaoxi |
author_facet |
XIAO Gaoxi Nur Diana Zainuren |
format |
Final Year Project |
author |
Nur Diana Zainuren |
author_sort |
Nur Diana Zainuren |
title |
Crash of social networks with cherished connections : a simulation study |
title_short |
Crash of social networks with cherished connections : a simulation study |
title_full |
Crash of social networks with cherished connections : a simulation study |
title_fullStr |
Crash of social networks with cherished connections : a simulation study |
title_full_unstemmed |
Crash of social networks with cherished connections : a simulation study |
title_sort |
crash of social networks with cherished connections : a simulation study |
publisher |
Nanyang Technological University |
publishDate |
2021 |
url |
https://hdl.handle.net/10356/149105 |
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1772827633084530688 |