Big Data Intelligence for Dynamic Networks: Graph Learning, Anomaly Detection, and Trustworthy Analytics

Networks naturally represent real-world big data problems in which entities interact through structural, temporal, semantic, and contextual relationships. Recent progress in graph learning, graph neural networks, temporal graph modeling, and AI-driven analytics has opened new ways to understand dynamic networked environments. Anomaly detection is increasingly critical for identifying fraud, misinformation, failures, and security threats across diverse domains. Major challenges remain, however, in processing capacity, interpretability, robustness, privacy, and real-time performance. This collection aims to connect methodological innovation with trustworthy, application-oriented network intelligence.Modern networked systems generate massive volumes of evolving, interconnected data, spanning social networks, financial transaction platforms, healthcare systems, transportation networks, and industrial IoT. Conventional static analytics often fail to capture changing relationships, hidden dependencies, and emerging risks. This Research Topic addresses these limitations by bringing together recent advances in big data intelligence. We aim to promote methods that are intelligent, efficient, explainable, and reliable for modeling, analyzing, and detecting complex behaviors in large-scale networked systems.This Research Topic welcomes original research on big data intelligence for dynamic and complex networks, including graph neural networks, dynamic graph learning, graph-based anomaly and fraud detection, explainable AI, and privacy-preserving network analytics. We also welcome work on streaming network analysis, knowledge graphs, and real-time monitoring. Contributions may cover social, financial, healthcare, smart city, and communication networks. Studies using real-world datasets, comparative evaluations, and high-performance implementations are particularly encouraged. Topic editors: Pooja Chaudhary, Kwok Tai Chui, Somya Sahoo Source: https://www.frontiersin.org/research-topics/84182/big-data-intelligence-for-dynamic-networks-graph-learning-anomaly-detection-and-trustworthy-analytics