A novel word ranking method based on distorted entropy

This paper proposes an application of distorted entropy as well-known tools for non-additive expected utility theory in word ranking. Our algorithms for two books “Statistical Inference” by Casella and Berger and “The Origin of Species” by Charles Darwin show that our method on the distorted entropy improves the corresponding ones in the literature.