Community detection in networks: A user guide
Community detection in networks is one of the most popular topics of modern network
science. Communities, or clusters, are usually groups of vertices having higher probability of …
science. Communities, or clusters, are usually groups of vertices having higher probability of …
Evolutionary computation for community detection in networks: A review
C Pizzuti - IEEE Transactions on Evolutionary Computation, 2017 - ieeexplore.ieee.org
In today's world, the interconnections among objects in many domains are often modeled as
networks, with nodes representing the objects and edges the existing relationships among …
networks, with nodes representing the objects and edges the existing relationships among …
A multiobjective evolutionary algorithm based on similarity for community detection from signed social networks
C Liu, J Liu, Z Jiang - IEEE transactions on cybernetics, 2014 - ieeexplore.ieee.org
Various types of social relationships, such as friends and foes, can be represented as
signed social networks (SNs) that contain both positive and negative links. Although many …
signed social networks (SNs) that contain both positive and negative links. Although many …
Vertex neighborhoods, low conductance cuts, and good seeds for local community methods
The communities of a social network are sets of vertices with more connections inside the
set than outside. We theoretically demonstrate that two commonly observed properties of …
set than outside. We theoretically demonstrate that two commonly observed properties of …
A review of heuristics and metaheuristics for community detection in complex networks: Current usage, emerging development and future directions
Sensibly highlighting the hidden structures of many real-world networks has attracted
growing interest and triggered a vast array of techniques on what is called nowadays …
growing interest and triggered a vast array of techniques on what is called nowadays …
A parallel multi-objective evolutionary algorithm for community detection in large-scale complex networks
Community detection in large-scale complex networks has recently received significant
attention as the volume of available data is becoming larger. The use of evolutionary …
attention as the volume of available data is becoming larger. The use of evolutionary …
Combining advanced computational social science and graph theoretic techniques to reveal adversarial information operations
Social media has influenced socio-political aspects of many societies around the world. It is
an effortless way for people to enhance their communication, connect with like-minded …
an effortless way for people to enhance their communication, connect with like-minded …
Fast local community discovery relying on the strength of links
Community detection methods aim to find nodes connected to each other more than other
nodes in a graph. As they explore the entire network, global methods suffer from severe …
nodes in a graph. As they explore the entire network, global methods suffer from severe …
Locating structural centers: A density-based clustering method for community detection
Uncovering underlying community structures in complex networks has received
considerable attention because of its importance in understanding structural attributes and …
considerable attention because of its importance in understanding structural attributes and …
Community detection using local neighborhood in complex networks
J Eustace, X Wang, Y Cui - Physica A: Statistical Mechanics and its …, 2015 - Elsevier
It is common to characterize community structure in complex networks using local
neighborhood. Existing related methods fail to estimate the accurate number of nodes …
neighborhood. Existing related methods fail to estimate the accurate number of nodes …