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Títol:	Exploring customer reviews for music genre classification and evolutionary studies
Autor/a:	Oramas, Sergio; Espinosa-Anke, Luis; Lawlor, Aonghus; Serra, Xavier; Saggion, Horacio
Abstract:	Comunicació presentada a la 17th International Society for Music Information Retrieval Conference (ISMIR 2016), celebrada els dies 7 a 11 d'agost de 2016 a Nova York, EUA.
Abstract:	In this paper, we explore a large multimodal dataset of about 65k albums constructed from a combination of Amazon customer reviews, MusicBrainz metadata and AcousticBrainz audio descriptors. Review texts are further enriched with named entity disambiguation along with polarity information derived from an aspect-based sentiment analysis framework. This dataset constitutes the cornerstone of two main contributions: First, we perform experiments on music genre classification, exploring a variety of feature types, including semantic, sentimental and acoustic features. These experiments show that modeling semantic information contributes to outperforming strong bag-of-words baselines. Second, we provide a diachronic study of the criticism of music genres via a quantitative analysis of the polarity associated to musical aspects over time. Our analysis hints at a potential correlation between key cultural and geopolitical events and the language and evolving sentiments found in music reviews.
Abstract:	This work was partially funded by the Spanish Ministry of Economy and Competitiveness under the Maria de Maeztu Units of Excellence Programme (MDM-2015-0502), by the TUNER project (TIN2015-65308-C5-5-R, MINECO/FEDER, UE), by the Keystone COST Action IC1302 and by the Insight Centre for Data Analytics under grant number SFI/12/RC/2289.
Matèries:	-Música -- Anàlisi
Drets:	© Sergio Oramas, Luis Espinosa-Anke, Aonghus Lawlor, Xavier Serra, Horacio Saggion. Licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). Attribution: Sergio Oramas, Luis Espinosa-Anke, Aonghus Lawlor, Xavier Serra, Horacio Saggion. “Exploring Customer Reviews for Music Genre Classification and Evolutionary Studies”, 17th International Society for Music Information Retrieval Conference, 2016. http://creativecommons.org/licenses/by/4.0/
Tipus de document:	Objecte de conferència Article - Versió publicada
Publicat per:	International Society for Music Information Retrieval (ISMIR)
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