# metadata.dc.description[].value
Treballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2019, Director: Jordi Nin

# metadata.dc.description.abstract[].value
[en] In an age where internet is a fundamental tool in the dissemination of information, musical trends can be affected by the viralization of songs and the appearance of emerging artists. This can mean that musical genres that were previously minority and even, occasionally, associated with marginal communities, can quickly become popular and remove this stigma. 
Many of these tendencies, which manage to emerge thanks to the Internet, sometimes cover the rest of the musical genres and give a false sense that«all music sounds the same». We listen the radio, we watch the television or we go to discos, and the music is always the same. But does that mean that there is only one musical style? In this study we are going to analyze a bit the musical panorama from the creation of a network, a graph, that will allow us to see which are the artists currently heard in the Last.fm[1] social network and the genres that predominate. We will base, therefore, on the data Last.fm make available to users to carry out this project.
We have also made an adaptation of the cultural diffusion algorithm of Axelrod [2], proposed in 1997, with the aim of predicting the musical evolution of the network and the new trends that will come in the future.
Finally we will see that, for the reasons discussed at the beginning, we can not know for sure what the future of the music industry will be, since there are factors exogenous to the data and the algorithm, which we will model
stochastically in our experiments.

# metadata.dc.rights[].value
memòria: cc-by-sa (c) Cristina Reina León, 2019

# metadata.dc.source[].value
Treballs Finals de Grau (TFG) - Enginyeria Informàtica