Thermo-Comparative Analysis of Texts: Translations and Target Readerships

Scaling laws have been an important topic in the physics community across a wide range of Fields. The dynamics
of several complex systems in biology, economics, and natural phenomena, have been described with relative
success using scaling laws. Scaling phenomena also emerge in the analysis of data associated with human
behavior, especially those containing a statistically distributed component, such as the number of links in
the World Wide Web or the size of cities. In current research, the analysis of scaling in data continues to
produce new and interesting Findings in a variety of scientific fields. In another multidisciplinary approach, the
usual concept of energy can be related to the frequency of word occurrence in a text, therefore, its probability
distribution can also be related with the temperature concept. We propose a comparative \"thermo-analysis\"
technique that allow us to determine the academic level of a text and its corresponding target readership in any
given language. We apply this technique to a large number of books by several authors and examine how the
vocabulary of a text changes when it is translated from one language to another. Unlike the uniform results
produced using the Zipf law, using our \"word energy\" distribution technique we find variations in the power-law
behavior. We also examine some common features that span across languages and identify some intriguing
questions concerning how to determine when a text is suitable for its intended readership.