Article
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A Model for Generating Playlists based on Consumer Emotions
Version 1
: Received: 7 March 2024 / Approved: 7 March 2024 / Online: 8 March 2024 (09:05:44 CET)
How to cite: Lugos Abarca, J.A. A Model for Generating Playlists based on Consumer Emotions. Preprints 2024, 2024030475. https://doi.org/10.20944/preprints202403.0475.v1 Lugos Abarca, J.A. A Model for Generating Playlists based on Consumer Emotions. Preprints 2024, 2024030475. https://doi.org/10.20944/preprints202403.0475.v1
Abstract
The article proposes a mathematical model for creating playlists based on the emotional utility of the consumer, aiming to maintain high user interest in music streaming platforms (Lugos Abarca, 2024). The proposed method follows these steps: first, it calculates the MEEPE of Songs on the digital platform; subsequently, it quantitatively defines the Consumer's MEEPI before exposure to music; then, it operates the MEEPE of the Songs with the consumer's initial MEEPI using the known resolution process (Lugos Abarca, 2023); finally, it employs an emotional utility function to determine possible levels of emotional satisfaction and establish the playback order. This results in the creation of an efficient theoretical model. It is recommended to expand the computational study of the model in future research by using a broader set of songs and considering various initial MEEPI of the consumer. The article's originality lies in its ability to predict, quantitatively and theoretically, the level of satisfaction a music consumer could experience when listening to a playlist.
Keywords
Single Equation Model, Decision Theory, Microeconomics, Utility Function, Neuroeconomics
Subject
Business, Economics and Management, Other
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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