Complex Networks of Words in Fables
This provides empirical insights into language evolution and textual analysis, but it is incremental as it applies existing methods to new data in a specific domain.
The study applied complex network theory to analyze two Ukrainian fables, finding that the language network is strongly correlated, scale-free, and small-world regardless of link representation.
In this chapter we give an overview of the application of complex network theory to quantify some properties of language. Our study is based on two fables in Ukrainian, Mykyta the Fox and Abu-Kasym's slippers. It consists of two parts: the analysis of frequency-rank distributions of words and the application of complex-network theory. The first part shows that the text sizes are sufficiently large to observe statistical properties. This supports their selection for the analysis of typical properties of the language networks in the second part of the chapter. In describing language as a complex network, while words are usually associated with nodes, there is more variability in the choice of links and different representations result in different networks. Here, we examine a number of such representations of the language network and perform a comparative analysis of their characteristics. Our results suggest that, irrespective of link representation, the Ukrainian language network used in the selected fables is a strongly correlated, scale-free, small world. We discuss how such empirical approaches may help form a useful basis for a theoretical description of language evolution and how they may be used in analyses of other textual narratives.