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Detecting Commmunities via Simultaneous Clustering of Graphs and Folksonomies
[article]
2008
We present a simple technique for detecting communities by utilizing both the link structure and folksonomy (or tag) information that is readily available in most social media systems. A simple way to describe our approach is by defining a community as a set of nodes in a graph that link more frequently to within this set than outside it and they share similar tags. Our technique is based on the Normalized Cut (NCut) algorithm and can be easily and efficiently implemented. We validate our
doi:10.13016/m2x34mw6k
fatcat:yjpk2hdmq5dzxnbjnedg2c7idq