Abstract

BARRAGAN, Mauricio Sánchez; CHANCHI, Gabriel Elías  and  CAMPO, Wilmar Yesid. Recommender system for musical contents based on the affective analysis of the social context. RISTI [online]. 2020, n.39, pp.100-113. ISSN 1646-9895.  https://doi.org/10.17013/risti.39.100-113.

Nowadays, thanks to the diffusion of social networks, it is necessary to take advantage of the social context of a user, in order to enrich decision-making in intelligent systems. Thus, this paper focuses on the affective study of the social context of a user, to enrich the recommendation of more relevant musical multimedia content. In this way, we propose as a contribution a system of recommendation of musical contents, which relates the sentimental analysis of the social context of a user through the social network twitter with the sentimental analysis of the lyrics of the songs. Thus, this paper presents the different components associated to the recommendation system, such as: musical content dataset, computational method based on a Bayesian classifier in charge of predicting musical contents from the analysis of the user's social context and online music service.

Keywords : context; musical contents; recommendation system; sentiment analysis.

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