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Identifying vital nodes in networks exhibiting a community structure is afundamental issue. Indeed, community structure is one of the main properties ofreal-world networks. Recent works have shown that community-aware centralitymeasures compare favorably with classical measures agnostic about thisubiquitous property. Nonetheless, there is no clear consensus about how theyrelate and in which situation it is better to use a classical or acommunity-aware centrality measure. To this end, in this paper, we perform anextensive investigation to get a better understanding of the relationshipbetween classical and community-aware centrality measures reported in theliterature. Experiments use artificial networks with controlled communitystructure properties and a large sample of real-world networks originating fromvarious domains. Results indicate that the stronger the community structure,the more appropriate the community-aware centrality measures. Furthermore,variations of the degree and community size distribution parameters do notaffect the results. Finally, network transitivity and community structurestrength are the most significant drivers controlling the interactions betweenclassical and community-aware centrality measures.

Characterizing the Interactions Between Classical and Community-aware Centrality Measures in Complex Networks