Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/28321
DC FieldValueLanguage
dc.contributor.authorJovanovska, Lidijaen_US
dc.contributor.authorEvkoski, Bojanen_US
dc.contributor.authorMirchev, Miroslaven_US
dc.contributor.authorMishkovski, Igoren_US
dc.date.accessioned2023-10-27T06:47:20Z-
dc.date.available2023-10-27T06:47:20Z-
dc.date.issued2020-02-22-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/28321-
dc.description.abstractAs Daniel J. Levitin noted, music is a cross-cultural phenomenon, a ubiquitous activity found in every known human culture. It is indeed, a living matter that flows through cultures, which makes it a complex system potentially holding valuable information. Therefore, we model country-to-country interactions to reveal macro-level music trends. The purpose of this paper is twofold. Firstly, we explore the way specific demographic characteristics, such as language and geographic location affect the global community structure in streaming service networks. Secondly, we examine whether a clear flow of musical trends exists in the world by identifying countries who are prominent leaders on the music streaming charts. The community analysis shows that there is strong support for the first claim. Next, we find that the flow of musical trends is not strongly directional globally, although we were still able to identify prominent leaders and followers within the communities. The obtained results can further lead to the development of more sophisticated music recommendation systems, kindle new cultural studies and bring discoveries in the field of musicology.en_US
dc.language.isoenen_US
dc.publisherSpringer, Chamen_US
dc.relation.ispartofseriesSpringer Proceedings in Complexity;-
dc.subjectMusicen_US
dc.subjectCommunity detectionen_US
dc.subjectLeader-follower relationshipen_US
dc.titleDemographic analysis of music preferences in streaming service networksen_US
dc.typeProceeding articleen_US
dc.relation.conferenceCompleNet 2020en_US
dc.identifier.doihttps://doi.org/10.1007/978-3-030-40943-2_20-
item.grantfulltextopen-
item.fulltextWith Fulltext-
crisitem.author.deptFaculty of Computer Science and Engineering-
crisitem.author.deptFaculty of Computer Science and Engineering-
Appears in Collections:Faculty of Computer Science and Engineering: Conference papers
Files in This Item:
File Description SizeFormat 
Complenet2020.pdf1.33 MBAdobe PDFView/Open
Show simple item record

Page view(s)

29
checked on May 9, 2024

Download(s)

21
checked on May 9, 2024

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.