What is centrality in graphs and why is it important?
An example of an AI chatbot conversation about centrality in graphs and its significance.
What is centrality in graphs and why is it important?
Centrality in graphs measures the importance of nodes within a network. It's crucial for understanding connectivity.
Can you explain the different types of centrality?
Sure! The main types are degree centrality, closeness centrality, betweenness centrality, and eigenvector centrality.
How do you calculate degree centrality?
Degree centrality is calculated by counting the number of edges connected to a node. Higher counts indicate more central nodes.
What applications does centrality have in real life?
Centrality is used in social network analysis, transportation networks, and even in epidemiology to track disease spread.
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