GRAPH NEURAL NETWORKS FOR CHURN CONTAGION PREDICTION IN TELECOMMUNICATIONS: A RELATIONAL LEARNING FRAMEWORK FOR CUSTOMER NETWORK ANALYSIS
Customer churn prediction in telecommunications has traditionally treated subscribers as independent entities, ignoring the relational structures—family plans, corporate accounts, and social referral networks—that govern collective departure behaviour. This article proposes a Graph Neural Network (GNN)–based framework...