Content-Based Authorship Identification for Short Texts in Social Media Networks

  1. José Gaviria de la Puerta 1
  2. Iker Pastor-López 1
  3. Javier Salcedo Hernández 1
  4. Alberto Tellaeche 1
  5. Borja Sanz 1
  6. Hugo Sanjurjo-González 1
  7. Alfredo Cuzzocrea 2
  8. Bringas, Pablo G. 1
  1. 1 Universidad de Deusto
    info

    Universidad de Deusto

    Bilbao, España

    ROR https://ror.org/00ne6sr39

  2. 2 University of Calabria
    info

    University of Calabria

    Cosenza, Italia

    ROR https://ror.org/02rc97e94

Libro:
Hybrid Artificial Intelligent Systems: 16th International Conference, HAIS 2021. Bilbao, Spain. September 22–24, 2021. Proceedings
  1. Hugo Sanjurjo González (coord.)
  2. Iker Pastor López (coord.)
  3. Pablo García Bringas (coord.)
  4. Héctor Quintián (coord.)
  5. Emilio Corchado (coord.)

Editorial: Springer International Publishing AG

ISBN: 978-3-030-86271-8,  978-3-030-86270-1

Año de publicación: 2021

Páginas: 27-37

Congreso: Hybrid Artificial Intelligent Systems (HAIS) (16. 2021. Bilbao)

Tipo: Aportación congreso

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Resumen

Today social networks contain a high number of false profiles that can carry out malicious actions on other users, such as radicalization or defamation. This makes it necessary to be able to identify the same false profile and its behaviour on different social networks in order to take action against it. To this end, this article presents a new approach based on behavior analysis for the identification of text authorship in social networks.

Fuente de los datos: Dialnet