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A Sound Prediction: EEG-Based Neural Synchrony Predicts Online Music Streams

Neuroforecasting predicts population-wide choices based on neural data of individuals and can be used, for example, in neuromarketing to estimate campaign successes. To deliver true value, the brain activity metrics should deliver predictive value above and beyond traditional stated preferences. Evi...

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Autores principales: Leeuwis, Nikki, Pistone, Daniela, Flick, Niels, van Bommel, Tom
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8354316/
https://www.ncbi.nlm.nih.gov/pubmed/34385953
http://dx.doi.org/10.3389/fpsyg.2021.672980
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author Leeuwis, Nikki
Pistone, Daniela
Flick, Niels
van Bommel, Tom
author_facet Leeuwis, Nikki
Pistone, Daniela
Flick, Niels
van Bommel, Tom
author_sort Leeuwis, Nikki
collection PubMed
description Neuroforecasting predicts population-wide choices based on neural data of individuals and can be used, for example, in neuromarketing to estimate campaign successes. To deliver true value, the brain activity metrics should deliver predictive value above and beyond traditional stated preferences. Evidence from movie trailer research has proposed neural synchrony, which compares the similarity of brain responses across participants and has shown to be a promising tool in neuroforecasting for movie popularity. The music industry might also benefit from these increasingly accurate success predictors, but only one study has been forecasting music popularity, using functional magnetic resonance imaging measures. Current research validates the strength of neural synchrony as a predictive measure for popularity of music, making use of electroencephalogram to capture moment-to-moment neural similarity between respondents while they listen to music. Neural synchrony is demonstrated to be a significant predictor for public appreciation on Spotify 3 weeks and 10 months after the release of the albums, especially when combined with the release of a single. On an individual level, other brain measures were shown to relate to individual subjective likeability ratings, including Frontal Alpha Asymmetry and engagement when combined with the factors artist and single release. Our results show the predictive value of brain activity measures outperforms stated preferences. Especially, neural synchrony carries high predictive value for the popularity on Spotify, providing the music industry with an essential asset for efficient decision making and investments, in addition to other practical implications that include neuromarketing and advertising industries.
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spelling pubmed-83543162021-08-11 A Sound Prediction: EEG-Based Neural Synchrony Predicts Online Music Streams Leeuwis, Nikki Pistone, Daniela Flick, Niels van Bommel, Tom Front Psychol Psychology Neuroforecasting predicts population-wide choices based on neural data of individuals and can be used, for example, in neuromarketing to estimate campaign successes. To deliver true value, the brain activity metrics should deliver predictive value above and beyond traditional stated preferences. Evidence from movie trailer research has proposed neural synchrony, which compares the similarity of brain responses across participants and has shown to be a promising tool in neuroforecasting for movie popularity. The music industry might also benefit from these increasingly accurate success predictors, but only one study has been forecasting music popularity, using functional magnetic resonance imaging measures. Current research validates the strength of neural synchrony as a predictive measure for popularity of music, making use of electroencephalogram to capture moment-to-moment neural similarity between respondents while they listen to music. Neural synchrony is demonstrated to be a significant predictor for public appreciation on Spotify 3 weeks and 10 months after the release of the albums, especially when combined with the release of a single. On an individual level, other brain measures were shown to relate to individual subjective likeability ratings, including Frontal Alpha Asymmetry and engagement when combined with the factors artist and single release. Our results show the predictive value of brain activity measures outperforms stated preferences. Especially, neural synchrony carries high predictive value for the popularity on Spotify, providing the music industry with an essential asset for efficient decision making and investments, in addition to other practical implications that include neuromarketing and advertising industries. Frontiers Media S.A. 2021-07-27 /pmc/articles/PMC8354316/ /pubmed/34385953 http://dx.doi.org/10.3389/fpsyg.2021.672980 Text en Copyright © 2021 Leeuwis, Pistone, Flick and van Bommel. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychology
Leeuwis, Nikki
Pistone, Daniela
Flick, Niels
van Bommel, Tom
A Sound Prediction: EEG-Based Neural Synchrony Predicts Online Music Streams
title A Sound Prediction: EEG-Based Neural Synchrony Predicts Online Music Streams
title_full A Sound Prediction: EEG-Based Neural Synchrony Predicts Online Music Streams
title_fullStr A Sound Prediction: EEG-Based Neural Synchrony Predicts Online Music Streams
title_full_unstemmed A Sound Prediction: EEG-Based Neural Synchrony Predicts Online Music Streams
title_short A Sound Prediction: EEG-Based Neural Synchrony Predicts Online Music Streams
title_sort sound prediction: eeg-based neural synchrony predicts online music streams
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8354316/
https://www.ncbi.nlm.nih.gov/pubmed/34385953
http://dx.doi.org/10.3389/fpsyg.2021.672980
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