Anomalies are rare observations (eg, data records or events) that deviate significantly from
the others in the sample. Over the past few decades, research on anomaly mining has …

Recently, the use of social networks such as Facebook, Twitter, and Sina Weibo has
become an inseparable part of our daily lives. It is considered as a convenient platform for …

Anomaly detection is an important problem that has been well-studied within diverse
research areas and application domains. The aim of this survey is two-fold, firstly we present …

Graph-based anomaly detection (GBAD) approaches are among the most popular
techniques used to analyze connectivity patterns in communication networks and identify …

The use of online social networks has made significant progress in recent years as the use
of the Internet has become widespread worldwide as the technological infrastructure and the …

Abstract Information cascades are important dynamical processes in complex networks. An
information cascade can describe the spreading dynamics of rumour, disease, memes, or …

Graph Neural Networks (GNNs) have become the leading paradigm for learning on (static)
graph-structured data. However, many real-world systems are dynamic in nature, since the …

The investigation of anomalies is an important element in many scientific research fields. In
recent years, this activity has been also extended to social networking and social …

Due to its importance in several applications, including fraud and spammer detection,
anomaly detection has emerged as a key challenge in social network analysis in recent …

Over the last few years, online social networks (OSNs), such as Facebook, Twitter and
Tuenti, have experienced exponential growth in both profile registrations and social …