Nowadays, online social media play a significant role in news broadcasts due to their
convenience, speed, and accessibility. Social media platforms leverage the rapid production …

We propose a scalable Gromov-Wasserstein learning (S-GWL) method and establish a
novel and theoretically-supported paradigm for large-scale graph analysis. The proposed …

Semi-implicit graph variational auto-encoder (SIG-VAE) is proposed to expand the flexibility
of variational graph auto-encoders (VGAE) to model graph data. SIG-VAE employs a …

Community Discovery is among the most studied problems in complex network analysis.
During the last decade, many algorithms have been proposed to address such task; …

Many complex networks in the real world have community structures–groups of well-
connected nodes with important functional roles. It has been well recognized that the …

Emotion is a status that combines people's feelings, thoughts, and behaviors, and plays a
crucial role in communication among people. Large studies suggest that human emotions …

Social media allow to fulfill perceived social needs such as connecting with friends or other
individuals with similar interests into virtual communities; they have also become essential …

Community detection in large-scale networks is one of the main challenges in social
networks analysis. Proposing a fast and accurate algorithm with low time complexity is vital …

A vital problem tackled in the network analysis literature is community structure identification
in social networks. There are many solutions to the community detection problem …

Emerging quantum processors provide an opportunity to explore new approaches for
solving traditional problems in the post Moore's law supercomputing era. However, the …