The paper introduces αTEC, a tensor-eigenvector centrality that interpolates between edge-driven and triangle-driven importance scores on connected graphs.
A new centrality measure based on the negative and positive effects of clustering coefficient for identifying influential spreaders in complex networks
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An $\alpha$-triangle eigenvector centrality of graphs
The paper introduces αTEC, a tensor-eigenvector centrality that interpolates between edge-driven and triangle-driven importance scores on connected graphs.