Abstract:
The quality of Wikipedia articles is manually evaluated which is
time inefficient as well as susceptible to human bias. An automated
assessment of these articles may help in minimizing the overall
time and manual errors. In this paper, we present a novel approach
based on the structural analysis of Wikigraph to automate the
estimation of the quality of Wikipedia articles. We examine the
network built using the complete set of English Wikipedia articles
and identify the variation of network signatures of the articles with
respect to their quality. Our study shows that these signatures are
useful for estimating the quality grades of un-assessed articles with
an accuracy surpassing the existing approaches in this direction.
The results of the study may help in reducing the need for human
involvement for quality assessment tasks
