Removing Specified Nodes in Complex Networks

In complex network analysis, selective node removal serves as a fundamental operation for investigating network structure and dynamic behavior. Nodes can be prioritized for removal using various evaluation criteria, including degree centrality (number of connections), authoritativeness metrics (e.g., PageRank or eigenvector centrality), or other topological measures. Implementation typically involves: 1. Calculating node scores using network analysis libraries (e.g., NetworkX's degree_centrality() or pagerank() functions) 2. Sorting nodes based on selected metrics 3. Removing target nodes through graph manipulation methods (e.g., remove_node() in NetworkX) This process enables examination of residual network properties, revealing critical connectivity patterns and robustness characteristics. The methodology supports applications in vulnerability analysis, community detection, and cascade effect studies by systematically testing network resilience under targeted node removal scenarios.