We suggest two approaches to the statistical analysis of texts, both based on the study of numerals occurrence in literary texts. The first approach is related to Benford’s Law and the analysis of the frequency distribution of various leading digits of numerals contained in the text. In coherent literary texts, the share of the leading digit 1 is even larger than prescribed by Benford’s Law and can reach 50 percent. The frequencies of occurrence of the digit 1, as well as, to a lesser extent, the digits 2 and 3, are usually a characteristic the author’s style feature, manifested in all (sufficiently long) literary texts of any author. This approach is convenient for testing whether a group of texts has common authorship: the latter is dubious if the frequency distributions are sufficiently different. The second approach is the extension of the first one and requires the study of the frequency distribution of numerals themselves (not their leading digits). The approach yields non-trivial information about the author, stylistic and genre peculiarities of the texts and is suited for the advanced stylometric analysis. The proposed approaches are illustrated by examples of computer analysis of the literary texts in English and Russian.

Two approaches to the statistical analysis of texts are suggested, both based on the study of numerals occurring in literary texts. The first approach is related to the study of the frequency distribution of various leading digits of numerals occurring in the text. This approach is convenient for testing whether a group of texts has common authorship: the latter is dubious if the frequency distributions are sufficiently different. The second approach requires the study of the frequencies of numerals themselves. The approach yields information about the author, stylistic and genre peculiarities of the texts and is suited for advanced study of authorial texts. The hypothesis that I. Ilf and E. Petrov are fake authors of novels "The Twelve Chairs" and "The Little Golden Calf", and they were ghosted by M. Bulgakov, is checked. The frequency distribution of numerals, as well as its cluster analysis, do not confirm this hypothesis.

Two approaches to the statistical analysis of texts are suggested, both based on the study of numerals occurrence in a coherent literary texts. The first approach is related to the analysis of the frequency distribution of various first significant digits of numerals occurring in the text. The frequencies of occurrence of the digit 1, as well as, to a lesser extent, the digits 2 and 3, are usually a characteristic author’s style feature, consistently manifested in all (sufficiently long) literary texts of any author. This approach is convenient for quick testing whether a group of texts has common authorship: the latter is dubious if the frequency distributions are sufficiently different. The second approach is the extension of the first one and requires the study of the frequency distribution of the numerals themselves (not their first significant digits). The approach yields non-trivial information about the author’s style peculiarities and is suited for the advanced study of authorial texts. The proposed approaches are illustrated by examples of computer analysis of the literary works by L. Dobychin and A. Platonov.

A new method of statistical analysis of texts is suggested. The frequency distribution of the first significant digits in numerals of connected authorial English-language texts is considered. Benford's law is found to hold approximately for these frequencies with a marked predominance of the digit 1. Deviations from Benford's law are statistically significant author peculiarities that allow, under certain conditions, to consider the problem of authorship and distinguish between texts by different authors. At the end of {1, 2,…, 8, 9} row, the digits distribution is subject to strong fluctuations and thus unrepresentative for our purpose. The approach suggested and the conclusions are backed by the examples of the computer analysis of works by W. M. Thackeray, M. Twain, R. L. Stevenson et al. The results are confirmed on the basis of non-parametric range Mann-Whitney and Kruskal-Wallis tests as well as the parametric Pearson's chi-squared test.