Several complex systems are characterized by presenting intricate
characteristics taking place at several scales of time and space. These
multiscale characterizations are used in various applications, including better
understanding diseases, characterizing transportation systems, and comparison
between cities, among others. In particular, texts are also characterized by a
hierarchical structure that can be approached by using multi-scale concepts and
methods. The multiscale properties of texts constitute a subject worth further
investigation. In addition, more effective approaches to text characterization
and analysis can be obtained by emphasizing words with potentially more
informational content. The present work aims at developing these possibilities
while focusing on mesoscopic representations of networks. More specifically, we
adopt an extension to the mesoscopic approach to represent text narratives, in
which only the recurrent relationships among tagged parts of speech (subject,
verb and direct object) are considered to establish connections among
sequential pieces of text (e.g., paragraphs). The characterization of the texts
was then achieved by considering scale-dependent complementary methods:
accessibility, symmetry and recurrence signatures. In order to evaluate the
potential of these concepts and methods, we approached the problem of
distinguishing between literary genres (fiction and non-fiction). A set of 300
books organized into the two genres was considered and were compared by using
the aforementioned approaches. All the methods were capable of differentiating
to some extent between the two genres. The accessibility and symmetry reflected
the narrative asymmetries, while the recurrence signature provided a more
direct indication about the non-sequential semantic connections taking place
along the narrative.

本文研究了如何使用多尺度方法来表征文本结构，进而通过对不同文学体裁作对比分析，使用可达性、对称性和重现度量这些多尺度概念和方法来区分小说和非小说文本的异同。