Analysis and Automatic Summary of Privacy Policies
Abstract
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. 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.
Copyright (c) 2023 Rodrigo Alfaro, René Venegas, Alan Bronfman, Miguel Valenzuela, Stephanie Riff, Enrique Sologuren
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
