Graph Neural Networks (GNNs) are commonly used and have shown promising
performance in recommendation systems. A major branch, Heterogeneous GNNs, models …

Region representations (also called embeddings) are useful for various urban computing
tasks. While graph-based region representation learning methods have shown outstanding …

Malicious social bots achieve their malicious purposes by spreading misinformation and
inciting social public opinion, seriously endangering social security, making their detection a …

The detection of automated accounts, also known as" social bots", has been an increasingly
important concern for online social networks (OSNs). While several methods have been …

With the rise and prevalence of social bots, their negative impacts on society are gradually
recognized, prompting research attention to effective detection and countermeasures …

In recent years, deep learning on graphs has achieved remarkable success in various
domains. However, the reliance on annotated graph data remains a significant bottleneck …

Anthropomorphic social bots are engineered to emulate human verbal communication and
generate toxic or inflammatory content across social networking services (SNSs). Bot …

Given the proliferation of AI-driven social bots, social media platforms face the dilemma of
whether disclosing bot identity can enhance transparency without undermining user …

Currently, due to the significant negative impact of social bots, there has been widespread
interest among researchers in automating the detection of social bots. And Graph Neural …

Currently, due to the significant negative impact of social bots, there has been widespread
interest among researchers in automating the detection of social bots. And Graph Neural …