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The identification of the most influential spreaders in networks is importantto control and understand the spreading capabilities of the system as well asto ensure an efficient information diffusion such as in rumor-like dynamics.Recent works have suggested that the identification of influential spreaders isnot independent of the dynamics being studied. For instance, the key diseasespreaders might not necessarily be so when it comes to analyze social contagionor rumor propagation. Additionally, it has been shown that different metrics(degree, coreness, etc) might identify different influential nodes even for thesame dynamical processes with diverse degree of accuracy. In this paper, weinvestigate how nine centrality measures correlate with the disease and rumorspreading capabilities of the nodes that made up different synthetic andreal-world (both spatial and non-spatial) networks. We also propose ageneralization of the random walk accessibility as a new centrality measure andderive analytical expressions for the latter measure for simple networkconfigurations. Our results show that for non-spatial networks, the $k$-coreand degree centralities are most correlated to epidemic spreading, whereas theaverage neighborhood degree, the closeness centrality and accessibility aremost related to rumor dynamics. On the contrary, for spatial networks, theaccessibility measure outperforms the rest of centrality metrics in almost allcases regardless of the kind of dynamics considered. Therefore, an importantconsequence of our analysis is that previous studies performed in syntheticrandom networks cannot be generalized to the case of spatial networks.

The role of centrality for the identification of influential spreaders in complex networks