RISTI - Revista Ibérica de Sistemas e Tecnologias de Informação
ISSN 1646-9895
BARRAGAN, Mauricio Sánchez; CHANCHI, Gabriel Elías CAMPO, Wilmar Yesid. Recommender system for musical contents based on the affective analysis of the social context. []. , 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.
: context; musical contents; recommendation system; sentiment analysis.