We present results of network analysis of Ukrainian texts. Autosemantic (meaningful) words are considered as network vertices connected with links when belonging to one sentence. Subnetworks corresponding to specific parts of speech (verbs, nouns, adjectives, etc.) are also built. The obtained networks are small-world and scale-free. To make comparisons, random texts with parameters corresponding to real texts are generated using several approaches. Various parameters of networks are calculated, including transitivity, betweenness, degree centralization, mean distance, network diameter, exponents of degree distribution, etc. Comparison of network parameters of real and generated texts shows that borders between them are quite fuzzy.

中文翻译：

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乌克兰语文本中自语义词网络的特性

我们展示了乌克兰文本的网络分析结果。自语义（有意义的）词在属于一个句子时被认为是与链接相连的网络顶点。还构建了对应于特定词性（动词、名词、形容词等）的子网络。获得的网络是小世界和无标度的。为了进行比较，使用几种方法生成具有与真实文本相对应的参数的随机文本。计算了网络的各种参数，包括传递性、介数、度集中度、平均距离、网络直径、度分布的指数等。真实文本和生成文本的网络参数比较表明它们之间的边界非常模糊。