An Edit-centric Approach for Wikipedia Article Quality Assessment

Edison Marrese-Taylor1, Pablo Loyola2, Yutaka Matsuo3
1The University of Tokyo, 2IBM Research, 3University of Tokyo


We propose an edit-centric approach to assess Wikipedia article quality as a complementary alternative to current full document-based techniques. Our model consists of a main classifier equipped with an auxiliary generative module which, for a given edit, jointly provides an estimation of its quality and generates a description in natural language. We performed an empirical study to assess the feasibility of the proposed model and its cost-effectiveness in terms of data and quality requirements.