  This article considers the fluctuation analysis methods of Taylor and Ebeling
& Neiman. While both have been applied to various phenomena in the statistical
mechanics domain, their similarities and differences have not been clarified.
After considering their analytical aspects, this article presents a large-scale
application of these methods to text. It is found that both methods can
distinguish real text from independently and identically distributed (i.i.d.)
sequences. Furthermore, it is found that the Taylor exponents acquired from
words can roughly distinguish text categories; this is also the case for
Ebeling and Neiman exponents, but to a lesser extent. Additionally, both
methods show some possibility of capturing script kinds.
