Inter-Clique Influence Networks
نویسندگان
چکیده
Cliques have interesting properties that make them an ideal subject for social network analysis. Their members are close-knit and share common interests, which makes cliques a potent force spreading influence. Since networks often contain multiple cliques, it is important to understand how they can influence one another. In this study, we propose model describes the opinion dynamics of interconnected cliques. The has two versions, with randomized other deterministic dynamics. We perform some analysis on their convergence demonstrate behaviors via simulations.
منابع مشابه
Clique Cover on Sparse Networks
We consider the problem of edge clique cover on sparse networks and study an application to the identification of overlapping protein complexes for a network of binary protein-protein interactions. We first give an algorithm whose running time is linear in the size of the graph, provided the treewidth is bounded. We then provide an algorithm for planar graphs with bounded branchwidth upon which...
متن کاملClique percolation in random networks.
The notion of k-clique percolation in random graphs is introduced, where k is the size of the complete subgraphs whose large scale organizations are analytically and numerically investigated. For the Erdos-Rényi graph of N vertices we obtain that the percolation transition of k-cliques takes place when the probability of two vertices being connected by an edge reaches the threshold p(c) (k) = [...
متن کاملParameterized Clique on Scale-Free Networks
Finding cliques in graphs is a classical problem which is in general NP-hard and parameterized intractable. However, in typical applications like social networks or protein-protein interaction networks, the considered graphs are scale-free, i.e., their degree sequence follows a power law. Their specific structure can be algorithmically exploited and makes it possible to solve clique much more e...
متن کاملConvolutional Neural Networks with Alternately Updated Clique
Improving information flow in deep networks helps to ease the training difficulties and utilize parameters more efficiently. Here we propose a new convolutional neural network architecture with alternately updated clique (CliqueNet). In contrast to prior networks, there are both forward and backward connections between any two layers in the same block. The layers are constructed as a loop and a...
متن کاملStatistical properties of random clique networks
In this paper, a random clique network model to mimic the large clustering coefficient and the modular structure that exist in many real complex networks, such as social networks, artificial networks, and protein interaction networks, is introduced by combining the random selection rule of the Erdös and Rényi (ER) model and the concept of cliques. We find that random clique networks having a sm...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications
سال: 2021
ISSN: ['2188-4730']
DOI: https://doi.org/10.5687/sss.2021.84