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Exploring customer reviews for music genre classification and evolutionary studies

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dc.contributor.author Oramas, Sergio
dc.contributor.author Espinosa-Anke, Luis
dc.contributor.author Lawlor, Aonghus
dc.contributor.author Serra, Xavier
dc.contributor.author Saggion, Horacio
dc.date.accessioned 2017-10-23T09:14:04Z
dc.date.available 2017-10-23T09:14:04Z
dc.date.issued 2016
dc.identifier.citation Oramas S, Espinosa-Anke L, Lawlor A, Serra X, Saggion H. Exploring customer reviews for music genre classification and evolutionary studies. In: Devaney J, Mandel MI, Turnbull D, Tzanetakis G, editors. ISMIR 2016. Proceedings of the 17th International Society for Music Information Retrieval Conference; 2016 Aug 7-11; New York City (NY). [Canada]: ISMIR; 2016. p. 150-6.
dc.identifier.uri http://hdl.handle.net/10230/33063
dc.description 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.
dc.description.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.
dc.description.sponsorship 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.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher International Society for Music Information Retrieval (ISMIR)
dc.relation.ispartof Devaney J, Mandel MI, Turnbull D, Tzanetakis G, editors. ISMIR 2016. Proceedings of the 17th International Society for Music Information Retrieval Conference; 2016 Aug 7-11; New York City (NY). [Canada]: ISMIR; 2016. p. 150-6.
dc.relation.isreferencedby http://hdl.handle.net/10230/34325
dc.rights © 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.
dc.rights.uri http://creativecommons.org/licenses/by/4.0/
dc.subject.other Música -- Anàlisi
dc.title Exploring customer reviews for music genre classification and evolutionary studies
dc.type info:eu-repo/semantics/conferenceObject
dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/TIN2015-65308-C5-5-R
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion

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