Complex networks pervade various real-world systems, from the natural environment to
human societies. The essence of these networks is in their ability to transition and evolve …

Predicting information cascade popularity is a fundamental problem in social networks.
Capturing temporal attributes and cascade role information (eg, cascade graphs and …

Abstract Information cascade size prediction is one of the primary challenges for
understanding the diffusion of information. Traditional feature‐based methods heavily rely …

Determining the damage level of the fire-damaged concrete structure is critical for the
structural assessment and repair of buildings after fire. Existing methods assess the damage …

Information dissemination refers to how information spreads among users on social
networks. With the widespread application of mobile communication and internet …

The ability to model the information diffusion process and predict its size is crucial to
understanding information propagation mechanism and is useful for many applications such …

Popularity prediction, which aims to forecast how many users would like to interact with a
target item or online content in the future, can help online shopping or social media …

Information diffusion prediction is a complex task due to the dynamic of information
substitution present in large social platforms, such as Weibo and Twitter. This task can be …

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 …

Trending topic diffusion and prediction analysis is an important problem and has been well
studied in social networks. Representation learning is an effective way to extract node …