Using Laplacian Spectra to Analyze Project Based Services

Abstract

In this paper, we use Laplacian spectral analysis to study the characteristics of complex service project networks by observing their marked signatures in the Laplacian eigenvalues and eigenvectors. Based on that, we also depict other representations of the complexity of those project complex networks including inverse participation ratio (IPR), degree expectation value (DEV). Compared with using adjacency matrix or coupling matrix only, we find that those extended spectral analysis methods do provide interesting features like lens to observe the intrinsic properties of the complex network representing the organizational structure of project based services.