Community detection aims at discovering the structure, behavior, dynamics, and
organization of a complex network by finding cohesive groups where nodes (entities) are, in …

In recent years, several organizations have implemented interventions aimed at integrating
work processes and bridging network clusters. These are often permeated by different …

The enormous growth of the Web led to the birth of different network structures. Therefore,
one of the important issues in the field of complex network analysis is to find and exploit the …

Community detection is an important problem in network science that discovers highly
clustered groups of nodes having similar properties. Label propagation algorithm (LPA) is …

Label propagation algorithm (LPA) has attracted much attention due to its linear time
complexity. However, there are disadvantages of uncertainty and randomness in the label …

Many algorithms have been developed to detect communities in networks. The success of
these developed algorithms varies according to the types of networks. A community …

The real‐world complex networks, such as biological, transportation, biomedical, web, and
social networks, are usually dynamic and change over time. The communities which reflect …

Community detection is one of the most essential issues in social networks analysis field.
Among the available categories of algorithms, the label propagation algorithm-based (LPA …

We propose a label propagation-based algorithm to extract community structure using a new
similarity measure based on centrality and common neighbours. Initially, a distinct label is …

One of the crucial research areas in the analysis of complex social networks is the
identification of communities. Since community detection is an NP-complete problem …