  This study proposes the usage of a method called VoteRank, created by Zhang
et al. (2016), to identify influential nodes on patent citation networks. In
addition, it proposes enhanced VoteRank algorithms, extending the Zhang et al.
work. These novel algorithms comprise a reduction on the voting ability of the
nodes affected by a chosen spreader if the nodes are distant from the spreader.
One method uses a reduction factor that is linear regarding the distance from
the spreader, which we called VoteRank-LRed. The other method uses a reduction
factor that is exponential concerning the distance from the spreader, which we
called VoteRank-XRed. By applying the methods to a citation network, we were
able to demonstrate that VoteRank-LRed improved performance in choosing
influence spreaders more efficiently than the original VoteRank on the tested
citation network.
