The network architecture of the human brain has become a feature of increasing interest to
the neuroscientific community, largely because of its potential to illuminate human cognition …

The development of new technologies for mapping structural and functional brain
connectivity has led to the creation of comprehensive network maps of neuronal circuits and …

Detecting and analyzing dense groups or communities from social and information networks
has attracted immense attention over the last decade due to its enormous applicability in …

Community structure is one of the most relevant features encountered in numerous real-
world applications of networked systems. Despite the tremendous effort of a large …

Community Discovery is among the most studied problems in complex network analysis.
During the last decade, many algorithms have been proposed to address such task; …

Clustering methods are applied regularly in the bibliometric literature to identify research
areas or scientific fields. These methods are for instance used to group publications into …

Many complex networks exhibit a modular structure of densely connected groups of nodes.
Usually, such a modular structure is uncovered by the optimization of some quality function …

Abstract “There can be no vulnerability without risk; there can be no community without
vulnerability; there can be no peace, and ultimately no life, without community.”-[M. Scott …

The COVID-19 pandemic has produced a flurry of online activity on social media sites. As
such, analysis of social media data during the COVID-19 pandemic can produce unique …

Nodes in real-world networks are repeatedly observed to form dense clusters, often referred
to as communities. Methods to detect these groups of nodes usually maximize an objective …