Quantitative approach to evaluating the influence of literary works using the graph theory

Authors

  • Ирина Леонидовна Каширина Voronezh State University image/svg+xml
  • Владислав Анатольевич Ковун Voronezh State University image/svg+xml

DOI:

https://doi.org/10.17308/sait.2019.3/1319

Keywords:

graph theory, books, analysis of social networks, centrality metrics, PageRa

Abstract

The success of books is most often measured by circulation, the number of copies sold, reprints, the availability of adaptations, etc. Such metrics may not be objective enough, since they are subject to external factors - such as marketing and the relevance of the work at the time of release. Moreover, these metrics are subject to distortion over time. This article proposes a quantitative approach to assessing the significance of literary works through the construction of a graph of influence and the calculation of various centrality indicators for such a graph. The proposed method is applied to a network containing links between more than 460,000 works of world science fiction. A list of the main books that can be considered the basis of the genre is obtained from this network. The results of the analysis of the influence of individual authors are also presented.

Author Biographies

  • Ирина Леонидовна Каширина, Voronezh State University

    Doctor of Technical Sciences, Professor, Department of Mathematical Methods Operations Research, Faculty of Applied mathematics, Informatics and mechanics, Voronezh State University

  • Владислав Анатольевич Ковун, Voronezh State University

    postgraduate student of the Department of Mathematical Methods Operations Research, Faculty of Applied mathematics, Informatics and mechanics, Voronezh State Universit

References

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Published

2019-08-23

Issue

Section

Computer Linguistics and Natural Language Processing

How to Cite

Quantitative approach to evaluating the influence of literary works using the graph theory. (2019). Proceedings of Voronezh State University. Series: Systems Analysis and Information Technologies, 3, 177-185. https://doi.org/10.17308/sait.2019.3/1319

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