t-learning

In the previous post I presented the use of folksonomy for tagging the DiTV programs, so that they could be automatically and semantically matched to a course ontology. However, it wasn’t very clear what it is and why it is useful, so today I’ll give a brief explanation on the subject.

A folksonomy consists of a series of pieces of information of any kind classified by users with labels. The labels space is plain – without hierarchy, in contrast with an ontology or taxonomy – and common among all the users. So, the term would explain this “classification made by people”, as marked by Quintarelli, though the term is attributed to Van der Wal and made popular by Gene Smith. Van der Wal defines it like this:

Folksonomy is the result of personal free tagging of information and objects (anything with a URL) for one’s own retrival. The tagging is done in a social environment (usually shared and open to others). Folksonomy is created from the act of tagging by the person consuming the information.

So, this proccess has two dimensions or steps – personal and social. First, the user marks a piece of information to have an easier access to it later. This kind of selfish behaviour would be the personomy. Then, and more interesting for the rest of the world, it also contributes to a wider classification of articles – the folksonomy.

It’s worth noting that there are two kinds of indexation made by humans – the tagging done by the creator and the one done by the community of viewers. Examples of the first are YouTube (videos), Flickr (pictures), or Tagzania (places). Examples of the second, which would be the more accurate folksonomy, are mainly bookmarking sites as del.icio.us or ma.gnolia. Now we are interested in the second type.

What do we achieve by doing this? It is clear that ambiguation and synonims may give some problems. Selfish tags like “important” or “mine”, that only helps a user to find their marked items, don’t give any benefit to the community. However, the greatest amount are describing tags that give an average view of what we can find in that item.