Best TU Berlin Student Research Ideas in Computational Music Studies

In this 20-minute session, the three most innovative research ideas for master's theses in computational music studies will be presented by their student authors from the Audio Communication and Technology programme at TU Berlin. This will be followed by a short award ceremony by the lecturer, who will explain the selection and the reasons for the first prize. The purpose of the session is to enable music technology students with innovative ideas to network with stakeholders from the music industry, acquire feedback, and potentially initiate future collaborations.
Selected contributions this year are as follows:
Niklas Werani: Local Connections as Explanatory Factors for Spotify Chart Success
Lotto Thomas: Playlisting Enbies. Investigating Gender Bias in Spotify's Curation with a Focus on Non-Binary Artists
Paula Gnoth: Human Curation in the Age of Algorithms: A Look at NTS Radio as Streaming Platforms Took Over