ARAPP: Análisis y Resumen Automático de Políticas de Privacidad

Rodrigo Alfaro, René Venegas, Alan Bronfman, Miguel Valenzuela, Stephanie Riff, Enrique Sologuren

Producción científica: Contribución a una revistaArtículorevisión exhaustiva

Resumen

A fundamental right of the users of computer applications is that they can know the privacy policies (PP) that such applications establish. It is particularly relevant that they know about the treatment that they accept regarding the use of their data. However, these PP are very extensive and written in administrative-legal and commercial language, which makes them difficult to read and understand. The aim of this paper is to automatically summarize the PPs of five social network applications (Facebook, Twitter, TikTok, Snapchat and Instagram) in spanish, through extractive and abstractive techniques. For this purpose, three representation approaches from Natural Language Processing are used, these are: Graph Analysis, TF-IDF and Gensim. Fifteen summaries were automatically generated and evaluated in order to measure the readability and relevance, by an expert in law, based on 20 questions prepared by a study of the University of Austin, Texas (Zaeem et al., 2018). Finally, based on a classification of each privacy policy according to different risk factors, the Gensim method is found to be the most suitable for the representation and summarization of the PP's. The PP of Snapchat is also identified as the application that best meets these risk factors.

Título traducido de la contribuciónAnalysis and Automatic Summary of Privacy Policies
Idioma originalEspañol
Páginas (desde-hasta)23-35
Número de páginas13
PublicaciónLinguamatica
Volumen14
N.º2
DOI
EstadoPublicada - 2022

Palabras clave

  • Gensim
  • automatic summarization
  • legal texts
  • private policies
  • risk factors
  • social networks

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