Internet and social media have become a widespread, large scale and easy to use platform
for real-time information dissemination. It has become an open stage for discussion …

The deluge of digital information in our daily life—from user-generated content, such as
microblogs and scientific papers, to online business, such as viral marketing and advertising …

Recent studies show that the predictive performance of graph neural networks (GNNs) is
inconsistent and varies across different experimental runs, even with identical parameters …

Information diffusion prediction is an important task, which studies how information items
spread among users. With the success of deep learning techniques, recurrent neural …

Researchers, enterprises, and governments have made great efforts to detect
misinformation promptly and accurately. Traditional solutions either examine complicated …

One important task in the study of information cascade is to predict the future recipients of a
message given its past spreading trajectory. While the network structure serves as the …

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

With the development of social networks, the spread of fake news brings great negative
effects to people's daily life, and even causes social panic. Fake news can be regarded as …

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

With the advancement of science and technology, the number of academic papers
published each year has increased almost exponentially. While a large number of research …