From Facebook friend circles to hidden influencer groups, community detection in social networks is evolving fast. Researchers are combining deep learning, graph neural networks, and advanced ...

Community detection — the task of finding groups of densely connected nodes in a network — has become a popular tool in urban analysis. Applied to street networks, it promises to reveal something ...

Abstract: Network traffic analysis plays a vital role in detecting malicious activities, anomalies, and understanding communication patterns. Two major classes of techniques, graph-based community ...

“Customer looking to replace 20-year-old furnace. No heat. Can’t afford a new system. Needs help.”“Has been clogged for about a week; yesterday it started getting bad. We were out there about a month ...

We propose a hybrid methodology to evaluate the alignment between structural communities inferred from interaction networks and the linguistic coherence of users' textual production in online social ...

ABSTRACT: Purpose: The purpose of this study is to develop a scalable, risk-aware artificial intelligence (AI) framework capable of detecting financial fraud in high-throughput digital transaction ...