Miedo (in)fundado al algoritmolas recomendaciones de YouTube y la polarización

  1. Javier García-Marín 1
  2. Ignacio-Jesús Serrano-Contreras 2
  1. 1 Universidad de Granada
    info

    Universidad de Granada

    Granada, España

    ROR https://ror.org/04njjy449

  2. 2 Grupo de Investigación SINAI, Universidad de Jaén
Journal:
Comunicar: Revista Científica de Comunicación y Educación

ISSN: 1134-3478

Year of publication: 2023

Issue Title: Educación para la ciudadanía digital: Algoritmos, automatización y comunicación

Issue: 74

Pages: 61-70

Type: Article

DOI: 10.3916/C74-2023-05 DIALNET GOOGLE SCHOLAR lock_openDialnet editor

More publications in: Comunicar: Revista Científica de Comunicación y Educación

Abstract

Social media have established a new way of communicating and understanding social relationships. At the same time, there are downsides, especially, their use of algorithms that have been built and developed under their umbrella and their potential to alter public opinion. This paper tries to analyse the YouTube recommendation system from the perspectives of reverse engineering and semantic mining. The first result is that, contrary to expectations, the issues do not tend to be extreme from the point of view of polarisation in all cases. Next, and through the study of the selected themes, the results do not offer a clear answer to the proposed hypotheses, since, as has been shown in similar works, the factors that shape the recommendation system are very diverse. In fact, results show that polarising content does not behave in the same way for all the topics analysed, which may indicate the existence of moderators –or corporate actions– that alter the relationship between the variables. Another contribution is the confirmation that we are dealing with non-linear, but potentially systematic, processes. Nevertheless, the present work opens the door to further academic research on the topic to clarify the unknowns about the role of these algorithms in our societies.

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Data source: Dialnet