Graphs, which encode pairwise relations between entities, are commonly utilized data structures in the realm of the Web and Social Media. As the most representative technique, graph machine learning methods have been extensively developed to effectively analyze graph patterns in a computational manner, which has achieved great success in numerous real-world applications. Meanwhile, the boom of large language models (LLMs) has revolutionized Natural Language Processing (NLP) and Artificial Intelligence (AI). Consequently, increasing attention has been paid to exploring the potential of leveraging LLMs for advancing graph machine learning techniques. This emerging intersection presents both opportunities and challenges that warrant attention and further exploration. To facilitate the research exchange in this exciting field, we propose the organization of a special topic at the WISE'2024 conference, titled "Graph Machine Learning on Web and Social Media". The goal of this special topic track is to bring together researchers from academia and practitioners from the industry, providing them with an opportunity to present their recent progress and share valuable insights related to advancements on the web and social media.
The special track will be welcoming theory, methodology and application papers falling into the scope of following themes, including but not limited to:
