[This post takes up some of the themes that Matt Webb, Paul Hammond, Matt Biddulph and I talked about in our paper at ETech 2005 on Reinventing Radio: Enhancing One-to-Many with Many-to-Many. A podcast of that talk is available.]
A few days ago I wrote about Phonetags, an experimental internal service that we’ve been running inside the BBC which allows you to bookmark, tag and rate songs you’ve heard on the radio with your mobile phone. Now I want to talk briefly a bit about one interesting way of using folksonomic tags that we developed conceptually while building the system.
The concept is really simple – there are concepts in the world that can be loosely described as being made up of aggregations of other smaller component concepts. In such systems, if you encourage the tagging of the smallest component parts, then you can aggregate those tags up through the whole system. You get – essentially – free metadata on a whole range of other concepts. Let me give you an example.
In Phonetags, we allow users to bookmark, rate and tag songs. They do so for a combination of personal gain and to add their voice to the collective. But music radio shows can be loosely understood as a collection of songs, and music radio networks can be equally understood as a collection of shows. So if ten songs that are well-rated and tagged with ‘alternative’ and ‘pop’ are played on one specific radio show, it’s quite plausible to argue that the show itself could be automatically understood as being tagged with ‘alternative’, ‘pop’ and that it should be considered well-rated. Similarly if all the shows are equally tagged with ‘alternative’, then it’s likely that you could describe the network that broadcasts them as an ‘alternative’ station.
How you handle the aggregation up the chain is an interesting question. My first instinct is that you would aggregate all the tags for a song, slice off the top ten or twenty and then throw away the rest and all the quantitative information. Then you do the same for all the other songs played in a show, and then reaggregate to see which tags have been played over the most songs. The alternative would be to simply add together all the tags that people sent in during that timeslot, but I think that would skew things towards the popular songs that people tagged a lot and wouldn’t necessarily reflect the character of the show itself. But that’s up for debate.
Another, and perhaps more intriguing, way of aggregating tags up through a conceptual chain would be to view albums as collections of songs and artists as a collection of albums/songs. This would mean that from the simple act of encouraging people to tag individual songs you were getting useful descriptive metadata on radio shows, radio networks, artists and albums:
The upshot of all of this is that you start getting a way of navigating between a whole range of different concepts based on these combinations of tags and ratings. The tags give you subject related metadata, the ratings give you qualitative metadata and from this you can start finding new ways to say, “If you liked this song, you may also like this album, network, album or artist“. You can start to generate journeys that move you from network to that networks most popular songs, through to the best albums on related themes (or which conjure similar moods or associations even if they’re by radically different artists) and so on.
And because you have a semantic understanding of the relationship between concepts like a ‘song’, an ‘album’ and an ‘artist’ you can allow people to drill-down or move up through various hierarchies of data and track the changes in an artist’s style over time. For me, this is a pretty compelling argument that understanding semantic relationships between concepts makes folksonomic tagging even more exciting, rather than less so, and may indicate a changing role for librarians towards owning formal conceptual relationships rather than descriptive, evocative metadata. But that’s a post for another time.
Are there other places where this kind of thing could be applied? Well, off the top of my head I can’t think of anything useful you could do with photographs, but I think folder structures on web-sites could prove an interesting challenge. I’d be fascinated to see if it would be possible to find well-structured websites with usefully nested folders and to aggregate tags from the individual pages up to section homepages and eventually to the site homepage. A little over a year ago I wrote about URL structure we developed for broadcast radio sites at the BBC built on the Programme Information Pages platform which you can see in action on the Radio 3 site. The URL structure mirrored a formal heirarchy much like the song / album / artist one – except for episode / programme brand and network. I’d be fascinated to know whether you could get a useful understanding of what Performance on 3 was about by aggregating all the tags from each of the episodes contained within its folder, and whether aggregating still further up to the frontpage of Radio 3 would give you a good description of the network’s philosophy and approach. One for Josh at del.icio.us, perhaps?
Now it’s over to you guys – can you think of any other heirarchies or places where we could encourage the tagging of the smallest practical component part and then derive value from aggregating up the semantic chain? Could the same thing work for non-heirarchic relationships? Anyone?
18 replies on “How to build on bubble-up folksonomies…”
In a museum context, perhaps you could aggregate upwards from: object > gallery > museum?
An added twist is that this hierachy isn’t constant over time, and so as objects get moved from gallery to gallery, or perhaps loaned to another museum, the aggregated tag collections would change.
Funny you should mention that, we just applied bubble up from posts to blogs to seed the Technorati blog finder
I’d love to hear your thoughts on it.
Relationships between people in social groups?
Magazine Programmes? TV Channels?
Well, how about sites on hosted services?
The most obvious example that springs to mind is LiveJournal. You know, “if you liked this post, you’ll like these authors”. Spreading up to “if you like this author, you’ll like these authors” and then maybe “if you like these authors, you might like this category/group/whatevertheycall them (I know they have some kind of grouping system)”. In the end, you can go from liking a selection of posts to discovering groups that might interest you.
Similarly, you couldn’t do it with photographs themselves, but you could do it on flickr in the context of photographs -> users -> groups – not finding you similar photos, but finding you users who produce similar photographs and ultimately similar groups of users who will produce photos you like.
But yeah, any hosted web service which usually follows some kind of hierarchy.
Amazon might be interesting, because genres/topics can cross media. And if readers are tagging stuff with what it’s *actually about* (which, let’s face it, the titles don’t necessarily tell you) then it has the potential to enhance their similarities engine. We like things for topics/authors/actors just as much as for what they are.
Books has got to be an area of opportunity. Tags on books will reflect on author and possibly on publisher.
TV Channels must be prime as well, with the proliferation of channels, it is getting increasingly diificult to seek out new and interesting content, much the same as radio and music.
Nice graphics by the way!
When I looked at your first image, I thought the people at the top were listeners rather than artists. Geographic data on listeners would allow the tags to bubble back to describe the taggers, to tag a listener, and then a geographic area, which could be used to discover market gaps where radio stations or shows could prosper. For example, if many people in a city are tagging a lot of disco, and there’s no station in the area playing disco, that might be a good indication that someone should start a disco station. With tags and tagged listeners mapped to time, an odd sort of radio station could be fully and automatically customized to the local listeners.
off the top of my head I can’t think of anything useful you could do with photographs
Well the folder and page idea is generic enough to apply to photos, albums and photographers.
You could use the upwardly mobile tag data to find photographers who do landscapes or those who do portraits.
If the photos are arranged well enough in containing albums which designate areas (e.g. New York Photos, Santorini Photos etc.) then the tag data welling up could indicate the area-type (New York == city, buildings, broadway; Santorini == island, volcano, caldera, donkeys) and that would be useful for less well known areas without having to specifically describe the area.
Interesting article. I think one challenge though is where do you stop and how much really applies. One super popular song could skew the station description.
I wonder if some sort of approach like this couldn’t be applied to speech radio. With 6music, you have the advantage that everything being tagged is a discrete entity in itself. Would something similar work for, say, tagging an edition of Any Questions, the World at One or 606? If you could tag programmes like that on a temporal basis (“from 15’20” to 18’12”, tag it with ‘Conservative leadership election’…”), bubbling up would produce some interesting stats not only on the content of each programme, but of contributors, public reactions to topics, and more…
It seems like it is facets more than hierarchies that are being discussed. With that it also seems like it would work in a flat structure much like del.icio.us and use the distinct data points of person tagging, bookmark, and tag term to do similar aggregations.
5D? 6D? more… 🙂
I’m sure that folksonomies in music could be used far more. But I like to categorise music with LOTS of tags: Country of Origin, Instruments, Time-signatures, Genre, even band members? That way, it becomes possible to search for “Swedish Folk-Rock Elvis-covers featuring didgeridoo” or whatever… And thats exactly what I want to do.
Unfortunately, the rest-of-the-world probbaly won’t enter as many tags as I would.
In Reader² I’m using facets for authors, literacy types and read statuses.
Thoughtful stuff as always. In the absence of trackbacks my comment is over here
Geography would seem at first to lend itself to a static hierarchy and strict taxonomical system, but as people amused by old maps will attest, Beyond This Point Be Dragons.
Another interesting outcome of bubbling up geographical tags: It would be easy to surface ‘disputed territories’ by pockets of conflicting tagging.
I know you posted this months ago, but I just reread it. Also, Mr. Hoodia, above, somehow snuck through.
hello guys! this forum is good, but i am a newbie in this thema.
Please, tell me where i can read more about this problema.
^^ many thanks, korra#@%@*^#@! ^^
Who can help me with .httpaccess ?
where i can fined full information about .httpaccess file syntaxis?