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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

On the role of words in the network structure of texts: Application to authorship attribution

Full text
Author(s):
Akimushkin, Camilo [1] ; Amancio, Diego R. [2] ; Oliveira, Jr., Osvaldo N. [1]
Total Authors: 3
Affiliation:
[1] Univ Sao Paulo, Sao Carlos Inst Phys, Ave Trabalhador Sao Carlense 400, Sao Carlos, SP - Brazil
[2] Univ Sao Paulo, Inst Math & Comp Sci, Ave Trabalhador Sao Carlense 400, Sao Carlos, SP - Brazil
Total Affiliations: 2
Document type: Journal article
Source: PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS; v. 495, p. 49-58, APR 1 2018.
Web of Science Citations: 1
Abstract

Well-established automatic analyses of texts mainly consider frequencies of linguistic units, e.g. letters, words, and bigrams. In a recent, alternative approach, medium and large-scale text structures were used in opposition to the belief that text structure is dominated by the language features. In this paper, we introduce a generalized similarity measure to compare texts which accounts for both the network structure of texts and the role of individual words in the networks. The similarity measure is used for authorship attribution of three collections of books, each composed of 8 authors and 10 books per author. High accuracy rates were obtained with typical values between 90% and 98.75%, much higher than with the traditional term frequency-inverse document frequency (tf-idf) approach for the same collections. These accuracies are also higher than those obtained solely with the topology of networks. We conclude that the different properties of specific words on the macroscopic scale structure of a whole text are as relevant as their frequency of appearance; conversely, considering the identity of nodes brings further knowledge about a piece of text represented as a network. (C) 2017 Elsevier B.V. All rights reserved. (AU)

FAPESP's process: 14/20830-0 - Using complex networks to recognize patterns in written texts
Grantee:Diego Raphael Amancio
Support Opportunities: Regular Research Grants
FAPESP's process: 13/14262-7 - Nanostructured films from biologically-relevant materials
Grantee:Osvaldo Novais de Oliveira Junior
Support Opportunities: Research Projects - Thematic Grants
FAPESP's process: 16/19069-9 - Using semantical information to classify texts modelled as complex networks
Grantee:Diego Raphael Amancio
Support Opportunities: Regular Research Grants