The 2019 anti-CAA protest in India witnessed massive Twitter participation from people on
both sides. It was unique compared to most online social movements that showcase …

Identifying the sources of propagation in social networks, such as the misinformation
propagation, is one of the key issues recently. Most existing studies assume the underlying …

Graph neural networks have demonstrated significant power in learning graph
representations for homogeneous networks. However, real-world network data can often be …

Motif detection is a graph algorithm that detects certain local structures in a graph. Although
network motif has been studied in graph analytics, eg, social network and biological …

Network motifs, as a fundamental higher-order structure in large-scale networks, have
received significant attention over recent years. Particularly in heterogeneous networks …

This study introduces a pioneering Time Series-based Transaction Pattern Analysis model
for scrutinizing profit dynamics within the pre-owned luxury goods domain via network …

This paper explores anomaly detection through temporal network analysis. Unlike many
conventional methods, relying on rule-based algorithms or general machine learning …

Network embedding has attracted a lot of attention in different fields recently. It represents
nodes in a network into a low-dimensional and dense space while preserving the structural …

With the rapid development of electronic payment, risks in large-scale financial transaction
networks are persistently arising. One important problem is how to use the transaction data …

This study introduces a pioneering Time Series-based Transaction Pattern Analysis model
for scrutinizing profit dynamics within the pre-owned luxury goods domain via network …