IVI is the first integrative method that captures all topological dimensions of a network. It synergizes six centrality measures while removing their inherent biases to identify the most influential nodes.
Measures how well-connected a node is to its direct neighbors. IVI integrates Degree Centrality and ClusterRank to capture local influence while correcting for clustering bias.
Captures influence beyond immediate neighbors. IVI integrates Neighborhood Connectivity and Local H-index to assess a node's power within its extended local environment.
Measures a node's position in the entire network topology. IVI integrates Betweenness Centrality and Collective Influence to capture global bridging and spreading power.
IVI = Hubness Score × Spreading Score. Hubness combines DC and LH-index; Spreading combines CR, NC, BC, and CI. This multiplicative integration ensures both local power and global reach.
| Method | Local | Semi-Local | Global | Bias Correction |
|---|---|---|---|---|
| Degree Centrality | ✓ | ✗ | ✗ | ✗ |
| Betweenness | ✗ | ✗ | ✓ | ✗ |
| PageRank | ✓ | ✗ | ~ | ✗ |
| K-shell | ✗ | ~ | ~ | ✗ |
| ★ IVI | ✓ | ✓ | ✓ | ✓ |
cent_network.vis() to color and size nodes by IVIinfluential package