Enhancing Music Recommender Systems with Personality Information and Emotional States: A Proposal.
Bruce Ferwerda, Markus Schedl · International Conference on User Modeling, Adaptation, and Personalization · 2014
This position paper describes the initial research assumptions to improve music recommendations by including personality and emotional states. By including these psychological factors, we believe that the accuracy of the recommendation can be enhanced. We will give attention to how people use music to regulate their emotional states, and how this regulation is related to their personality. Furthermore, we will focus on how to acquire data from social media (i.e., microblogging sites such as Twitter) to predict the current emotional state of users. Finally, we will discuss how we plan to connect the correct emotionally laden music pieces to support the emotion regulation style of users.