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Exploring Centrality Metrics and Machine Learning in Network Analysis
This chapter investigates the complexities of network analysis, focusing on centrality metrics and their relevance in criminal networks. It also examines the innovative 'Finder' method, which applies machine learning to enhance targeting strategies while contrasting traditional metrics with contemporary approaches in network science.