Abstract：The eigenvalues and eigenvectors of Laplacian matrix of a complex network contain information about its topology and collective behavior. In this paper， for the evolving Chinese linguistic networks， spectral density， spectral order， and eigenvectors of their Laplacian matrices are studied. Interestingly， the spectra concentrate on the interva [0， 3]， and the sum of spectral density on [0， 3] decreases successively with the expansion of network size. If the eigenvalues are listed in decreasing order， then the top eigenvalues follow a power-law distribution， while the other top eigenvalues and the middle part satisfy exponential distributions. The change trend of the degrees and the eigenvectors corresponding to the top three eigenvalues is variety. Moreover， these results are compared with those of the adjacency matrices.
2021, Vol. 55 
