1. I made a reading list about folksonomy at my CGL blog or del.icio.us. I will update the list frequently by adding related articles.
2. Characteristics of Folksonomy Network
The folksonomy networks show the following characteristics:
a. Small-world Network
Almost similar with a random network but having much larger clustering co-efficient factor. I.e., Small shortest path but a larger clustering coefficient.
b. Scale-free Network
A scale-free network is a network in which any two nodes can be connected no matter what the system size is. This is because there is a node called "hub"which is a highly connected node than any others. In folksonomies, popular keywords can act like this hub and thus the network shows scale-free network properties.
A scale-free network shows the following rules:
(1) Power law : Degree distribution follows the Yule-Simon distribution, which is called a power law: P(k) ~ k^(-r), where k is a degree of connectivity of a node and P(k) is it's probability
(2) Preferential Attachment : A way to build a scale-free network. The idea is to make a connection with a more connected node.
3. Next step
a. Build a simple graph by using CITEAM tag data
b. Find some algorithms about recommendation
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