Online social networking platforms have drastically facilitated the phenomenon of
information cascades, making cascade prediction an important task for both researchers and …

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

Supervised learning, while prevalent for information cascade modeling, often requires
abundant labeled data in training, and the trained model is not easy to generalize across …

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

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 …

The online social platforms, like Twitter, Facebook, LinkedIn and WeChat, have grown really
fast in last decade and have been one of the most effective platforms for people to …

The method of combining RNN and GNN for information cascade prediction can
simultaneously model and represent temporal and spatial information, demonstrating good …

Information propagation on social networks could be modeled as cascades, and many
efforts have been made to predict the future popularity of cascades. However, most of the …

Accurate prediction of what types of patents that companies will apply for in the next period
of time can figure out their development strategies and help them discover potential partners …

Online social media have significantly boosted the creation and transmission of information,
accelerating the dissemination and interaction of vast amounts of data, thereby making the …