Table 1 Feature metrics of the top 10 high-centrality regional nodes

From: Passenger flow distribution forecasting at integrated transport hub via group evolution mechanism and multimodal data

Node

Degree centrality

Betweenness centrality

Closeness centrality

Eigenvector centrality

8

0.421

0.306

0.527

0.391

11

0.368

0.454

0.593

0.435

10

0.316

0.227

0.501

0.311

20

0.263

0.084

0.463

0.306

15

0.263

0.125

0.380

0.168

13

0.263

0.159

0.487

0.256

19

0.263

0.127

0.463

0.271

6

0.211

0.079

0.452

0.221

4

0.158

0.007

0.373

0.165

1

0.157

0.017

0.432

0.222

  1. Degree centrality represents the proportion of a node’s neighbors to all possible connections. Betweenness centrality measures how often a node serves as the “shortest-path bridge” between pairs of nodes in the network. Closeness centrality reflects the average length of the shortest paths from a node to every other node in the network. Eigenvector centrality is derived from the leading eigenvector of the network’s adjacency matrix and evaluates centrality by considering both the number of a node’s connections and the importance of the nodes it connects to.
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