An Edit-centric Approach for Wikipedia Article Quality Assessment

Edison Marrese-Taylor, Pablo Loyola, Yutaka Matsuo


Abstract
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.
Anthology ID:
D19-5550
Volume:
Proceedings of the 5th Workshop on Noisy User-generated Text (W-NUT 2019)
Month:
November
Year:
2019
Address:
Hong Kong, China
Editors:
Wei Xu, Alan Ritter, Tim Baldwin, Afshin Rahimi
Venue:
WNUT
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
381–386
Language:
URL:
https://aclanthology.org/D19-5550
DOI:
10.18653/v1/D19-5550
Bibkey:
Cite (ACL):
Edison Marrese-Taylor, Pablo Loyola, and Yutaka Matsuo. 2019. An Edit-centric Approach for Wikipedia Article Quality Assessment. In Proceedings of the 5th Workshop on Noisy User-generated Text (W-NUT 2019), pages 381–386, Hong Kong, China. Association for Computational Linguistics.
Cite (Informal):
An Edit-centric Approach for Wikipedia Article Quality Assessment (Marrese-Taylor et al., WNUT 2019)
Copy Citation:
PDF:
https://aclanthology.org/D19-5550.pdf
Attachment:
 D19-5550.Attachment.pdf