Bogdanov, DmitrySerra, Xavier2017-10-112017-10-112017Bogdanov D, Serra X. Quantifying music trends and facts using editorial metadata from the Discogs database. In: Hu X, Cunningham SJ, Turnbull D, Duan Z. ISMIR 2017 Proceedings of the 18th International Society for Music Information Retrieval Conference; 2017 Oct 23-27; Suzhou, China. [Suzhou]: ISMIR; 2017. p. 89-95.9789811151798http://hdl.handle.net/10230/32931Comunicació presentada a: ISMIR 2017, celebrat a Suzhou, Xina, del 23 al 27 d'octubre de 2017While a vast amount of editorial metadata is being actively gathered and used by music collectors and enthusiasts, it is often neglected by music information retrieval and musicology researchers. In this paper we propose to explore Discogs, one of the largest databases of such data available in the public domain. Our main goal is to show how largescale analysis of its editorial metadata can raise questions and serve as a tool for musicological research on a number of example studies. The metadata that we use describes music releases, such as albums or EPs. It includes information about artists, tracks and their durations, genre and style, format (such as vinyl, CD, or digital files), year and country of each release. Using this data we study correlations between different genre and style labels, assess their specificity and analyze typical track durations. We estimate trends in prevalence of different genres, styles, and formats across different time periods. In our analysis of styles we use electronic music as an example. Our contribution also includes the tools we developed for our analysis and the generated datasets that can be re-used by MIR researchers and musicologists.application/pdfeng© Dmitry Bogdanov, Xavier Serra. Licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). Attribution: Dmitry Bogdanov, Xavier Serra. “Quantifying music trends and facts using editorial metadata from the Discogs database”, 18th International Society for Music Information Retrieval Conference, Suzhou, China, 2017.info:eu-repo/semantics/conferenceObjectMusic metadataMusic genresComputational musicologyMusic information retrievalMusic datasetsinfo:eu-repo/semantics/openAccess