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The subject of this chapter is bibliographic corpus analysis, with data from the Polish national bibliography from the period 1801–2019. The research allowed us to discover and compare quantitative characteristics of the bibliographic corpus and of the reference corpus of general language. It was shown that the two corpora differ significantly. In particular, differences in the share of particular parts of speech and of the frequency distribution of lexemes were demonstrated. The statistical distributions of word spectra were also studied. The best fit was obtained for generalized inverse Gauss-Poisson and Zipf-Mandelbrot distributions. The analysis of parameters of both distributions for bibliographic and reference corpora also revealed differences between them. The best perspective for future research on bibliographic corpora is, apart from quantitative linguistics, semantic analysis and text-mining.

The subject of this chapter is the application of automatic taxonomy methods to the corpus of microtexts, consisting of book titles. We test two hypotheses. The first one claims that simply on the basis of a book title one can automatically recognize its genre (writing species). The second assumes the possibility of recognizing the author’s gender on the basis of the book’s title. FastText and word2vec methods were applied. The analyses give a positive (and rather astonishing) result: with properly chosen n-grams more than 70% of titles could be correctly assigned a writing species, while the accuracy of the gender recognition of the author was almost 80%. Both values significantly exceed the levels of random recognition. The research was conducted on the corpus of titles derived from the Polish national bibliography.