On the "Calligraphy" of Books

Abstract

Authorship attribution is a natural language processing task that has been widely studied, often by considering small order statistics. In this paper, we explore a complex network approach to assign the authorship of texts based on their mesoscopic representation, in an attempt to capture the flow of the narrative. Indeed, as reported in this work, such an approach allowed the identification of the dominant narrative structure of the studied authors. This has been achieved due to the ability of the mesoscopic approach to take into account relationships between different, not necessarily adjacent, parts of the text, which is able to capture the story flow. The potential of the proposed approach has been illustrated through principal component analysis, a comparison with the chance baseline method, and network visualization. Such visualizations reveal individual characteristics of the authors, which can be understood as a kind of calligraphy.

Text characterization based on recurrence networks

“…In [10], for example, the authors apply image analysis techniques to network visualizations in order to extract topological features of the mesoscopic networks to tackle the authorship recognition problem. Still in the context of this problem, in [21], the authors make use of the ability of the mesoscopic network to capture a narrative's story flow and, hence, the author's "calligraphy". Finally, in [6], the mesoscopic networks are used to study and analyze texts while considering the overall narrative and its unfolding along time.…”

Development of new models for authorship recognition using complex networks

“…Finally, unweighted networks can be obtained following specific processes. For instance, the edges with the lowest weights can be removed in order to obtain a fixed percentage of edges or to reach a given average degree (ARRUDA et al, 2017;MARINHO et al, 2017). Figure 7-e shows the obtained unweighted network with average degree equals to 2.…”

“…• Marinho, V. Q., de Arruda, H. F., Lima, T. S., Costa, L. da F., Amancio, D. R. (2017). In addition, the following publications were developed in collaboration with other researchers:…”