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Tad Hogg and Gabor Szabo
Social Computing Laboratory, HP Labs
Abstract
Web sites where users create and rate content as well as
form networks with other users display long-tailed distributions of
user activity. Using data from one such community site, Essembly, we
propose and evaluate mechanisms for these distributions that rely
only on information actually available to users. For Essembly, we
describe the scale-free degree distribution of the social network as
a result of users' shared interests, manifested by their content
rating activity. We find the long tails in network properties arise
from user activity rates that are broadly distributed, as well as
the extensive variability in the time users devote to the site.
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