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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.)

Character networks and book genre classification

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Author(s):
Holanda, Adriano J. [1] ; Matias, Mariane [2] ; Ferreira, Sueli M. S. P. [3] ; Benevides, Gisele M. L. [4] ; Kinouchi, Osame [2]
Total Authors: 5
Affiliation:
[1] Univ Sao Paulo, Dept Comp & Matemat, FFCLRP, Av Bandeirantes 3900, BR-14040901 Ribeirao Preto, SP - Brazil
[2] Univ Sao Paulo, Dept Fis, FFCLRP, Av Bandeirantes 3900, BR-14040901 Ribeirao Preto, SP - Brazil
[3] Univ Sao Paulo, Dept Educ Informacao & Comunicao, FFCLRP, Av Bandeirantes 3900, BR-14040901 Ribeirao Preto, SP - Brazil
[4] Univ Sao Paulo, Prefeitura Campus USP Ribeirao Preto, Av Bandeirantes 3900, BR-14040901 Ribeirao Preto, SP - Brazil
Total Affiliations: 4
Document type: Journal article
Source: INTERNATIONAL JOURNAL OF MODERN PHYSICS C; v. 30, n. 8 AUG 2019.
Web of Science Citations: 0
Abstract

We compared the social character networks of biographical, legendary and fictional texts in search for marks of genre differentiation. We examined the degree distribution of character appearance and found a power-law-like distribution that does not depend on the literary genre. We also analyzed local and global complex network measures, in particular, correlation plots between the recently introduced Lobby index and degree, betweenness and closeness centralities. Assortativity plots, which previous literature claims to separate fictional from real social networks, were also studied. We found no relevant differences among genres for the books studied when applying these network measures and we provide an explanation why the previous assortativity result is not correct. (AU)

FAPESP's process: 13/07699-0 - Research, Innovation and Dissemination Center for Neuromathematics - NeuroMat
Grantee:Oswaldo Baffa Filho
Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC