In recent years, we have witnessed an overwhelming and fast proliferation of different types
of malware targeting organizations and individuals, which considerably increased the time …

Abstract The study of Online Social Networks offers growing opportunities to examine a
number of aspects of the real world and to better understand how human society works at …

Community detection algorithms are essential tools that allow us to discover organizational
principles in networks. Today, in most cases, social networks are modeled as a multi …

The development of knowledge sharing platforms, like scientific social networks encourages
researchers to establish international collaboration in scientific projects. After reviewing the …

Modern data analysis and processing tasks typically involve large sets of structured data.
Graphs provide a powerful tool to describe the structure of such data, where the entities and …

Community detection algorithms play an important role in revealing and analyzing complex
network structures. However, when these algorithms are put into practice, privacy concerns …

Learners' community choice has a crucial role in e‐learning effectiveness. Indeed, individual
and structural factors (ie, learners pre‐existing profiles and networks of interactions) …

Attributed multiplex graph clustering, which partitions graph nodes from different
relationships into different clusters with each cluster retaining structure closeness and …

Security measurement models (SMMs) and quantitative security metrics (QSMs) are crucial
pillars of systematic security measurement. How to design the enhanced SMMs and effective …

Complex network analysis is a thriving research field, with a particular focus on community
detection. This paper addresses the challenge of community detection in multiplex networks …