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From entity extraction to network analysis: a method and an application to a Portuguese textual source

Author

Listed:
  • Conceição Rocha

    (FEP-UP; LIAAD/INESC)

  • Alípio Mário Jorge

    (FCUP; LIAAD/INESC)

  • Márcia Oliveira

    (FEP-UP; LIAAD/INESC)

  • Paula Brito

    (FEP-UP)

  • João Gama

    (FEP-UP, LIAAD/INESC)

  • Carlos Pimenta

    (FEP-UP, OBEGEF)

Abstract

This paper reports advances in the entity extraction task (named entity identification) of a text mining process that aims at unveiling non-trivial semantic structures, such as relationships and interaction between entities or communities. We proposed a 3-phase method that is applicable to the Portuguese language and potentially applicable to other languages as well. The method relies on flexible pattern matching, part-of-speech tagging, lexical-based rules and distance-based entity name merging. All steps are implemented using free software and taking advantage of various existing packages. Evaluation of the efficacy of the entity extraction method on part of a book written in portuguese indicates improved F1 results. For further evaluation and illustration of the usefulness of the proposed method, it is applied to a book on Freemasonry and observe the differences in the entity word clouds produced. We also define a social network of named entities solely from information contained in the book and extract structural insights that reveal connections, relationships and communities between entities.

Suggested Citation

  • Conceição Rocha & Alípio Mário Jorge & Márcia Oliveira & Paula Brito & João Gama & Carlos Pimenta, 2014. "From entity extraction to network analysis: a method and an application to a Portuguese textual source," OBEGEF Working Papers 032, OBEGEF - Observatório de Economia e Gestão de Fraude;OBEGEF Working Papers on Fraud and Corruption.
  • Handle: RePEc:por:obegef:032
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    File URL: http://www.fep.up.pt/repec/por/obegef/files/wp032.pdf
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    References listed on IDEAS

    as
    1. Feinerer, Ingo & Hornik, Kurt & Meyer, David, 2008. "Text Mining Infrastructure in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 25(i05).
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