Wednesday, March 07, 2007

Collabularies

Paul Anderson writes, " ...there is a distinction between a folksonomy (a collection of tags created by an individual for their own personal use) and a collabulary (a collective vocabulary)."

He expands, " We are also beginning to see compromise solutions known as collabulary in which a group of domain users and experts collaborate on a shared vocabulary with help of classification specialists."

Beth Kanter picks up on this and observes, "The... point makes we wonder about the difference in terms of behaviors and values in tagging communities versus crowd filtering communities (e.g digg)."

I noticed this as well and wondered about it.

It is important to distinguish between a network behaviour, such as the folksonomy as described above, and a group behaviour.

A collection of tags may be created in two very distinct ways:

1. people, working independently, just happen to use the same word to describe the same resource

2. people, working together, agree on a term that describes a given (type of) resource

Method number (1) is a folksonomy, and it is a network behaviour. It does not involve collaboration of any sort.

Method number (2) is not, strictly speaking, a folksonomy. It is a method more common to librarians and taxonomers.

We have seen, however, efforts made to organize tags (people will write, "Everybody tag this event 'OCC2007' or whatever).

This sort of organization is arguably no longer a folksonomy, as some people are using a privileged position to instruct other people how to tag (I discuss this in my paper here: http://www.downes.ca/post/14 )

I would not go so far as to use a word like 'collabulary' - that is a ridiculous word, and is not needed to describe something that we already have perfectly good words for, a 'taxonomy' or a 'vocabulary'.

And the author's suggestion that folksonomies ought to be recognized as 'collabularies' is, in my view, a mistake: it either misrepresents what a folksonomy is, or it uses a new word needlessly.

A community of individuals working independently, such as Digg users, is not collaborating. The rankings are not the result of group action. Rather, each person works independently.

Indeed, it is worth pointing out that when Digg members collaborate, the system is deemed to be broken and the reliability of the rankings cast in doubt. And interesting debate surrounds edge cases (such as the case where one person sees that another has Dug a resource, and, trusting the other person, Diggs the resource, not because it is good, but because people who Digg popular resources early are rated higher than people who don't).



1 comment:

  1. Thanks so much for linking to my blog- it has helped me discover a great new blog to read- yours.
    You make an interesting point about Digg users collaborating or colluding being perceived as negative. This is because Digg brings an enormous amount of traffic, and with that traffic there is an economic incentive to get content to the front page. Compare that to Connotea, which functions exclusively as an academic resource. With the economic/advertising incentives removed, Connotea encourages users to collaborate and create tag structures that you rightly call something other than folksonomies. Here's an interesting thing about Digg you may not have been aware of- aside from the psychological effect of Diggers befriending and Digging stories by top users, the underlying Digg algorithms themselves actually give more weight to stories submitted by top users. That is stories submitted by users who have submitted front page stories in the past are more likely to get promoted to the top.
    As for the concept of collaburaries, most of the time(and I have no hard evidence to back this up), they arise organically through folksonomic methods. That is, new vocabulary is largely embraced by community leaders after it has become somewhat prevalent in the community, rather than important individuals coining new terms outright.

    ReplyDelete

I welcome your comments - I'm really sorry about the moderation, but Google's filters are basically ineffective.