Skip to content

What we can learn from Folksonomy

Outward-facing Questions:

  • The great thing about delicious and folksonomy is that it creates an ontology as an emergent biproduct of individual self-serving efforts (that is, personal bookmarking). I’m wondering if we can take a similar tact to solve other AI problems.

Inward-facing Questions:

  • What is the best way to represent the evolution of a tag’s meaning (evolution on both the individual and group scale). Folksonomy is a lot more dynamic than a fixed ontology, so we might not be able to use the same old tools.
  • Folksonomy is the relationship between three types of information: tags, tagged objects, and the users who tag them. What information can we derive each that are not explicit in the structure. You can call this “tag grouping”, “neighbor search”, “related items”… but it’s really all just clustering. What are the differences when you cluster each?
  • Continuing from the last quesiton: it’s most intuitive to hierarchically cluster tags—this maps well onto the formal “ontology” model that information architects and NLP researchers are comfortable in dealing with. But what happens when we hierarchically cluster users and tagged items? What does hierarchy infer about the relationships between parents, children, and siblings in the resulting structure?
  • What are the differences in (tags, users, items) between digg, delicious, flickr, and citeulike?

Ah, to have time to pursue these….