PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Modeling the structure and evolution of discussion cascades.
V. Gomez, Bert Kappen and A. Kaltenbrunner
In: ACM Conference on Hypertext and Hypermedia, 22nd, 2011, 2011.

Abstract

We analyze the structure and evolution of discussion cascades in four popular websites: Slashdot, Barrapunto, Me- neame and Wikipedia. Despite the big heterogeneities between these sites, a preferential attachment (PA) model with bias to the root can capture the temporal evolution of the observed trees and many of their statistical properties, namely, probability distributions of the branching factors (degrees), subtree sizes and certain correlations. The parameters of the model are learned efficiently using a novel maximum likelihood estimation scheme for PA and provide a figurative interpretation about the communication habits and the resulting discussion cascades on the four different websites.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Learning/Statistics & Optimisation
ID Code:8307
Deposited By:Bert Kappen
Deposited On:14 October 2011