Research on Discrimination of Scientific Papers Based on Laplacian Spectrum Analysis
基于拉普拉斯谱分析的真伪科学论文甄别研究

This paper studies the Laplacian spectrum of scientific papers’ word co-occurrence network from three aspects: the Laplacian spectrum rank, the Laplace spectral density, and the Laplacian extremal eigenvalues. Through comparative analysis, the Laplacian spectral features of scientific papers’ word co-occurrence network are obviously different, and these differences can be used for discriminating the authenticity of scientific paper.