Abstract
How can social media be used to reveal latent social and collective perspectives on music? Our work addresses this question by introducing a Twitter dataset surrounding the Top 2000, a yearly national broadcasting event in The Nether-
lands. The Top 2000 is recognised as a valuable case study into the role of music as a social nostalgia-inducing phenomenon, triggering collective and autobiographical memories. Our dataset, containing enriched Twitter information
over the Top 2000 voting and broadcasting timeline in 2015, demonstrates how the broad audience support of the event enables data-oriented studies of the public response to and public signicance of the aired songs.
lands. The Top 2000 is recognised as a valuable case study into the role of music as a social nostalgia-inducing phenomenon, triggering collective and autobiographical memories. Our dataset, containing enriched Twitter information
over the Top 2000 voting and broadcasting timeline in 2015, demonstrates how the broad audience support of the event enables data-oriented studies of the public response to and public signicance of the aired songs.
Original language | English |
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Title of host publication | WebSci '16 |
Subtitle of host publication | Proceedings of the 8th ACM Conference on Web Science |
Place of Publication | New York, NY |
Publisher | Association for Computing Machinery (ACM) |
Pages | 296-300 |
Number of pages | 5 |
ISBN (Electronic) | 978-1-4503-4208-7 |
DOIs | |
Publication status | Published - 2016 |
Event | 8th ACM Web Science Conference, WebSci 2016 - Hannover, Germany Duration: 22 May 2016 → 25 May 2016 |
Conference
Conference | 8th ACM Web Science Conference, WebSci 2016 |
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Country/Territory | Germany |
City | Hannover |
Period | 22/05/16 → 25/05/16 |
Keywords
- social media
- data analysis
- music preferences