Hello,

I am a PhD student at the Music Technology Group (MTG) of the University Pompeu Fabra (UPF) in Barcelona. I am part of the MIR (Music Information Research) lab, and I am currently working with the TROMPA (Towards Richer Online Music Public-domain Archives) Project, an international research project, sponsored by the European Union, investigating how make public-domain digital music resources more accessible.


In my PhD work, titled “Assessing the Impact of Music Recommendation Diversity”, I am researching what have been the consequences of the introduction of recommendation technologies, increasingly part of the listening experience of people all over the world, especially in the context of streaming services.

Recommender systems’ role is to help users in finding music that can fit their interests and tastes, but Western-centric perspectives in systems’ design are often subject to criticism because of their power of reinforcing already existing cultural bias and therefore potentially impacting negatively on the music distribution mechanisms.

In this research, we aim to address the problem of assessing the impact of music recommendation diversity, or the lack thereof. This requires:
1) the formalization of a working definition of diversity in the music field
2) the development of evaluation practices for estimating diversity in the context of music recommender systems
3) the observation of emerging impact due to music recommendation diversity
4) the proposal of countermeasures for mitigating negative or reinforcing positive impact observed

Basing on already known consequences of the use of information technologies in political, economic and social areas, our goal is to understand the cultural impact that music recommender systems can have on our society.


Here what has been my journey until now:

Worklin


My top recommended references:

  1. Benjamin, W. (1969). The Work of Art in the Age of Mechanical Reproduction, translated by Harry Zohn, from the 1935 essay. Hannah Arendt, ed., Illuminations. London: Fontana. (pdf)
  2. Molino, J., Underwood, J., & Ayrey, C. (1990). Musical fact and the semiology of music. Music Analysis, 9(2), 105–156. (pdf)
  3. Celma, O., & Cano, P. (2008). From hits to niches? or how popular artists can bias music recommendation and discovery. In 2nd Workshop on Large-Scale Recommender Systems and the Netflix Prize Competition (ACM KDD). (pdf)
  4. Schmit, S., & Riquelme, C. (2017). Human Interaction with Recommendation Systems. In Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS) 2018. (pdf)