  We present results from our quantitative study of statistical and network
properties of literary and scientific texts written in two languages: English
and Polish. We show that Polish texts are described by the Zipf law with the
scaling exponent smaller than the one for the English language. We also show
that the scientific texts are typically characterized by the rank-frequency
plots with relatively short range of power-law behavior as compared to the
literary texts. We then transform the texts into their word-adjacency network
representations and find another difference between the languages. For the
majority of the literary texts in both languages, the corresponding networks
revealed the scale-free structure, while this was not always the case for the
scientific texts. However, all the network representations of texts were
hierarchical. We do not observe any qualitative and quantitative difference
between the languages. However, if we look at other network statistics like the
clustering coefficient and the average shortest path length, the English texts
occur to possess more clustered structure than do the Polish ones. This result
was attributed to differences in grammar of both languages, which was also
indicated in the Zipf plots. All the texts, however, show network structure
that differs from any of the Watts-Strogatz, the Barabasi-Albert, and the
Erdos-Renyi architectures.
