I’ve been writing a few (pending) pieces on user interfaces and social networks, and where they seem to be going. There’s been a lot of buzz recently about Schulze & Webb’s Olinda social radio project, which is a online listening software realised in hardware. It takes cues about your interest in a station by looking at volume levels; the idea being that the volume you listen at reflects your interest in that station.
Last.fm started out with a similar concept; listening to the entirety of a song was also a ‘preference’ vote (or that you were away from your computer, how can you tell the difference?), and that skipping a song indicated you didn’t like it. These are quite harsh metrics; there could be other reasons for skipping a song (you’re not in the right mood, you have a twitchy mouse finger) so it’s not necessarily an analogue for voting.
However, I’m particularly enamoured of two things happening here; user-generated metrics and passive data gathering. User-generated metrics is the idea that users and their behaviour in an electronic space provide very tangible feedback about their relationship to those spaces. The classic example is Amazon’s recommendation engine – people who bought that also bought this – but there are many abstracts ways this information can be gathered, and what it can mean. Passive data gathering is the idea that, like the example above, the way people interact with devices (and interfaces) provide a great deal of extraneous objective information, which could not be gathered should the same information was expressed in explicit terms. ‘Skip this song’ says so much more than a form which assessed your liking of the current song, and whether you’d like to hear it again in a week, month or year. Just skip it; if I skip it again, I don’t want to hear it.
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