UvA WG 2 - Music recommendation systems

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    UvA WG 2 - Music recommendation systems - Presentation Transcript

    1. Oriëntatie Nieuwe Media WG 2 Anne Helmond, Universiteit van Amsterdam, 17 februari.
    2. Discussed article Wall-Smith, Mat, Ross Rudesch Harley and Andrew Murphie. 'LAST.FM and the Music Multiverse'. Proceedings of the 3rd Art of Record Production Conference Queensland University of Technology, Brisbane Dec. 2007.
    3. Hoorcollege 3 + hoofdstuk 3 Flew (2008) • Technological determinism versus social shaping of technology (p. 43-44) • Marshall McLuhan and Raymond Williams (p. 46-49) • How do we place McLuhan and Williams in the technological determinism versus social change debate? • The medium is the message - McLuhan (p. 47) • Remediation (Bolter & Grusin, 1999) - zie hoorcollege sheets
    4. HC: Alternative histories But the rise of multi-user music communities can be usefully situated within a slightly different set of histories. That alternative history foregrounds collective effort, open databases and community participation. (p. 1)
    5. The Long Tail - Chris Anderson The 'long tail' is the mass of recorded music that was inaccessible or out of print prior to the affordances of network distribution. (p. 4)
    6. The Long Tail The Long Tail is a consumer demographic in business. The term was coined by Chris Anderson in the Wired article ‘The Long Tail’ in 2004. An example of a power law graph being used to demonstrate ranking of popularity. To the right is the long tail, to the left are the few that dominate (also known as the 80-20 rule). Source: Wikipedia
    7. ‘LAST FM and the Music Universe’ [...] we see the status of music shift from product to process, from consumption to participation, from object to a network-of-relations. (p. 2) networked music ecology (p. 2) Three steps are barriers in realizing a new music industry: (p. 4) 1. Production 2. Distribution 3. Discovery
    8. You are what you listen to? The original power in the Last.fm engine was its ability to move beyond the performance aspect that usually operates in any online profiling engine. By ’scrobbling’ data automatically, based on the users actual listening history, the engine avoided the usual quirks of a more ‘reflexive’ self-profiling. (p. 6) Last.fm affective features: skip/love/ban
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