A critical aspect of graph neural networks (GNNs) is to enhance the node representations by
aggregating node neighborhood information. However, when detecting anomalies, the …

Over the past decade, detecting fake reviews has emerged as a critical challenge in
ensuring the credibility of online businesses. The capability of Graph Neural Networks …

Although fraudulent operations on e-commerce platforms have been repeatedly mentioned,
neither its causes nor the complexity among merchants has been systematically established …

Graph Convolutional Networks (GCNs) are a popular type of machine learning models that
use multiple layers of convolutional aggregation operations and non-linear activations to …

Spam reviews have long polluted review systems, undermining their industries. Detecting
spam movie reviews faces some brand-new challenges compared to traditional spam …

In the age of the infodemic, it is crucial to have tools for effectively monitoring the spread of
rampant rumors that can quickly go viral, as well as identifying vulnerable users who may be …

Graph anomaly detection (GAD) has gained increasing attention in various attribute graph
applications, ie, social communication and financial fraud transaction networks. Recently …

This paper develops a theoretical model of determinants influencing multimodal fake review
generation using the theories of signaling, actor-network, motivation, and human …

Graph anomaly detection is crucial in many high-impact applications across diverse fields. In
anomaly detection tasks, collecting plenty of annotated data tends to be costly and …

In the age of the infodemic, it is crucial to have tools for effectively monitoring the spread of
rampant rumors that can quickly go viral, as well as identifying vulnerable users who may be …