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

User modeling (UM) aims to discover patterns or learn representations from user data about
the characteristics of a specific user, such as profile, preference, and personality. The user …

Rating platforms enable large-scale collection of user opinion about items (eg, products or
other users). However, untrustworthy users give fraudulent ratings for excessive monetary …

Online reviews capture the testimonials of" real" people and help shape the decisions of
other consumers. Due to the financial gains associated with positive reviews, however …

Given a bipartite graph of users and the products that they review, or followers and
followees, how can we detect fake reviews or follows? Existing fraud detection methods …

The spread of malicious or accidental misinformation in social media, especially in time-
sensitive situations, such as real-world emergencies, can have harmful effects on individuals …

Many online applications, such as online social networks or knowledge bases, are often
attacked by malicious users who commit different types of actions such as vandalism on …

Online reviews are an important source for consumers to evaluate products/services on the
Internet (eg Amazon, Yelp, etc.). However, more and more fraudulent reviewers write fake …

Social bots represent a new generation of bots that make use of online social networks
(OSNs) as command and control (C&C) channels. Malicious social bots have been used as …

Detecting anomalies on graph data has two types of methods. One is pattern mining that
discovers strange structures globally such as quasi-cliques, bipartite cores, or dense blocks …