Table 1.
The 18 centrality measures used in this study.
| Centrality name | Year | References | Based on |
|---|---|---|---|
| Subgraph | 2005 | Estrada and Rodriguez-Velazquez, 2005 | Eigenvalues to count close walks |
| Geodesic K-Path | 2006 | Borgatti and Everett, 2006 | Number of nodes reachable via shortest path of bounded length |
| Maximum neighborhood component | 2008 | Lin et al., 2008 | Size of the largest connected component within the direct neighbors of a given node |
| Density of maximum neighborhood component | Lin et al., 2008 | Ratio of edges to nodes within the largest connected component between a node's neighbors | |
| Decay | Jackson, 2010 | Proximity between a given node and every other node, weighted by a decay rate | |
| Topological coefficient | 2009 | Zhuge and Zhang, 2009 | Average number of neighbors of a given node that are also neighbors to a different node |
| Lobby Index | Campiteli et al., 2013 | Largest integer k such that the node has at least k neighbors with a degree of at least k. | |
| Coreness | 2010 | Kitsak et al., 2010 | Sum of k-shell indexes of a given node's neighbors |
| Leverage | Joyce et al., 2010 | Degree of a node relative to its neighbors | |
| Group | Narayanam and Narahari, 2010 | Game theory, to measure the marginal increase in group influence | |
| Wiener Index | 2011 | Caporossi et al., 2012 | Average distance from a given node to all other nodes |
| K-Path | Alahakoon et al., 2011 | Number of random paths of length k from all nodes that include a given node | |
| Diffusion Degree | Kundu et al., 2011 | Degree contribution of a node and its neighbors, weighted by a propagation probability | |
| LeaderRank | Lü et al., 2011 | Convergence of a random walk | |
| Laplacian | Gutman and Zhou, 2006 | Degrees of a node and its neighbors. Equivalent to using eigenvalues in the Laplacian | |
| Local Bridging | 2016 | Macker, 2016 | Ratio of shortest paths going through a node, modulated by its degree and degree of neighbors |
| VoteRank | Zhang et al., 2016 | Spreading ability, measuring by the convergence of an election process between neighbors. | |
| Heatmap | 2020 | Durón, 2020 | Sum of distance from a node to all others (i.e., farness) and average farness of the neighbors. |
Divisions in the table emphasize publication years.