  Targeting influential nodes in complex networks allows fastening or hindering
rumors, epidemics, and electric blackouts. Since communities are prevalent in
real-world networks, community-aware centrality measures exploit this
information to target influential nodes. Researches show that they compare
favorably with classical measures that are agnostic about the community
structure. Although the diffusion process is of prime importance, previous
studies consider mainly the famous Susceptible-Infected-Recovered (SIR)
epidemic propagation model. This work investigates the consistency of previous
analyses using the popular Linear Threshold (LT) propagation model, which
characterizes many spreading processes in our real life. We perform a
comparative analysis of seven influential community-aware centrality measures
on thirteen real-world networks. Overall, results show that Community-based
Mediator, Comm Centrality, and Modularity Vitality outperform the other
measures. Moreover, Community-based Mediator is more effective on a tight
budget (i.e., a small fraction of initially activated nodes), while Comm
Centrality and Modularity Vitality perform better with a medium to a high
fraction of initially activated nodes.
