  There is great significance in evaluating a node's Influence ranking in
complex networks. Over the years, many researchers have presented different
measures for quantifying node interconnectedness within networks. Therefore,
this paper introduces a centrality measure called Tr-centrality which focuses
on using the node triangle structure and the node neighborhood information to
define the strength of a node, which is defined as the summation of Gruebler's
Equation of the node's one-hop triangle neighborhood to the number of all the
edges in the subgraph. Furthermore, we socially consider it as the local trust
of a node. To verify the validity of Tr-centrality [1], we apply it to four
real-world networks with different densities and shapes, and Tr-centrality has
proven to yield better results.
