Misinformation such as fake news and rumors is a serious threat for information ecosystems
and public trust. The emergence of large language models (LLMs) has great potential to …

It is commonly perceived that fake news and real news exhibit distinct writing styles, such as
the use of sensationalist versus objective language. However, we emphasize that style …

Social media is one of the main sources for news consumption, especially among the
younger generation. With the increasing popularity of news consumption on various social …

Graph mining tasks arise from many different application domains, including social
networks, biological networks, transportation, and E-commerce, which have been receiving …

Abstract Knowledge tracing (KT) is a crucial task in online education that traces students'
evolving cognition changes over time. However, it is a challenging task due to the …

The surge in detecting fake news on social networks leads to increased research attention,
particularly in the realm of deep learning models based on graph neural networks (GNNs) …

Recent analyses have disclosed that existing rumor detection techniques, despite playing a
pivotal role in countering the dissemination of misinformation on social media, are …

Graph adversarial attack and defense is a research direction which has been widely
concerned in graph data field in recent years. With the popularity and application of graph …