Social Network Analysis

Social network analysis (SNA) uses graph-based methods to study relationships and patterns within interconnected systems, aiming to understand network structure, dynamics, and influence. Current research emphasizes developing robust and efficient algorithms, such as graph neural networks (GNNs) and clustering techniques, to analyze large-scale networks, detect misinformation, and address challenges like data imbalance and privacy concerns. SNA finds applications in diverse fields, including public health, political science, and marketing, providing valuable insights into complex social phenomena and informing data-driven decision-making.