Self-Organized Criticality in Small-World Networks Based on the Social Balance Dynamics

2011 ◽  
Vol 28 (11) ◽  
pp. 118901 ◽  
Author(s):  
Qing-Kuan Meng
Keyword(s):  
Small World ◽  
Small World Networks ◽  
Self Organized ◽  
The Social ◽  
Self Organized Criticality ◽  
Social Balance ◽  
Balance Dynamics

STABILITY IN THE SOCIAL PERCOLATION MODELS FOR TWO TO FOUR DIMENSIONS

2000 ◽  
Vol 11 (02) ◽  
pp. 287-300 ◽  
Author(s):  
ZHI-FENG HUANG
Keyword(s):  
Percolation Threshold ◽  
Percolation Model ◽  
Four Dimensions ◽  
Self Organized ◽  
The Social ◽  
Self Organized Criticality

The social percolation model proposed by Solomon et al. as well as its modification are studied in two to four dimensions for the phenomena of self-organized criticality. Stability in the models is obtained and the systems are shown to automatically drift towards the percolation threshold.

scholarly journals Online Rebellion: Self-Organized Criticality of Contemporary Protest Movements

SAGE Open ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 215824402092335
Author(s):  
Dmitry Zhukov ◽  
Konstantin Kunavin ◽  
Sergey Lyamin
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
Protest Movements ◽  
Self Organized ◽  
The Social ◽  
Self Organized Criticality ◽  
Mass Actions ◽  
Protest Activity

The theory of self-organized criticality (SOC) is applicable for explaining powerful surges of protest activity on social media. The objects of study were two protest clusters. The first was a set of Facebook groups that promoted the impeachment of the Brazilian president Dilma Rousseff. The second was a set of groups on the social network Vkontakte that provided support for anti-government rallies in Armenia, referred to as Electric Yerevan. Numerous groups in the examined clusters were functioning in SOC mode during certain periods. Those clusters were able to generate information avalanches—seemingly spontaneous, powerful surges of creation, transmission, and reproduction of information. The facts are presented that supported the assumptions that SOC effects in social networks are associated with mass actions on the streets, including violence. The observations of SOC make it possible to reveal certain periods when the course of a sociopolitical system is least stable.

scholarly journals An Advanced Algorithm for Higher Network Navigation in Social Internet of Things Using Small-World Networks

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 2007 ◽  
Author(s):  
Farhan Amin ◽  
Rashid Abbasi ◽  
Abdul Rehman ◽  
Gyu Sang Choi
Keyword(s):  
Internet Of Things ◽  
Social Networking ◽  
Social Networking Sites ◽  
Small World ◽  
Clustering Coefficient ◽  
Small World Networks ◽  
Single Node ◽  
The Social ◽  
Social Internet Of Things ◽  
The Right

The Internet of Things (IoT) is a recent evolutionary technology that has been the primary focus of researchers for the last two decades. In the IoT, an enormous number of objects are connected together using diverse communications protocols. As a result of this massive object connectivity, a search for the exact service from an object is difficult, and hence the issue of scalability arises. In order to resolve this issue, the idea of integrating the social networking concept into the IoT, generally referred as the Social Internet of Things (SIoT) was introduced. The SIoT is gaining popularity and attracting the attention of the research community due to its flexible and spacious nature. In the SIoT, objects have the ability to find a desired service in a distributed manner by using their neighbors. Although the SIoT technique has been proven to be efficient, heterogeneous devices are growing so exponentially that problems can exist in the search for the right object or service from a huge number of devices. In order to better analyze the performance of services in an SIoT domain, there is a need to impose a certain set of rules on these objects. Our novel contribution in this study is to address the link selection problem in the SIoT by proposing an algorithm that follows the key properties of navigability in small-world networks, such as clustering coefficients, path lengths, and giant components. Our algorithm empowers object navigability in the SIoT by restricting the number of connections for objects, eliminating old links or having fewer connections. We performed an extensive series of experiments by using real network data sets from social networking sites like Brightkite and Facebook. The expected results demonstrate that our algorithm is efficient, especially in terms of reducing path length and increasing the average clustering coefficient. Finally, it reflects overall results in terms of achieving easier network navigation. Our algorithm can easily be applied to a single node or even an entire network.

Scaling behaviors and self-organized criticality of two-dimensional small-world neural networks

2020 ◽  
Vol 540 ◽  
pp. 123191 ◽  
Author(s):  
Hong-Li Zeng ◽  
Chen-Ping Zhu ◽  
Shu-Xuan Wang ◽  
Yan-Dong Guo ◽  
Zhi-Ming Gu ◽  
...  
Keyword(s):  
Neural Networks ◽  
Small World ◽  
Two Dimensional ◽  
Self Organized ◽  
Self Organized Criticality
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