Automatic Quality Assessment of Wikipedia Articles—A Systematic Literature Review

PM Moás, CT Lopes - ACM Computing Surveys, 2023‏ - dl.acm.org
Wikipedia is the world's largest online encyclopedia, but maintaining article quality through
collaboration is challenging. Wikipedia designed a quality scale, but with such a manual …

Is cross-linguistic advert flaw detection in Wikipedia feasible? A multilingual-BERT-based transfer learning approach

M Li, H Zhou, J Hou, P Wang, E Gao - Knowledge-Based Systems, 2022‏ - Elsevier
Wikipedia is one of the most prominent online platforms from which people acquire
knowledge; thus, its article quality should be of great concern. Currently, many scholars …

A hybrid approach to classifying Wikipedia article quality flaws with feature fusion framework

P Wang, M Li, X Li, H Zhou, J Hou - Expert Systems with Applications, 2021‏ - Elsevier
Article quality has always been a major concern for Wikipedia. To improve article quality, it is
critical to first identify defects. Thus, flaw classification has attracted considerable attention …

Leveraging Large Language Models and Deep Learning for Wikipedia Quality Assessment

T Gunatilaka, S Ahangama… - 2024 6th International …, 2024‏ - ieeexplore.ieee.org
As of 2024, Wikipedia hosts over 60 million articles across 326 language editions, growing
to approximately 1.8 million new articles annually. While traditional encyclopedias rely on …

[PDF][PDF] Automatic Quality Assessment of Wikipedia Articles-A Systematic Literature

PM MOÁS, CT LOPES‏ - rdm.inesctec.pt
This document supplements the article entitled “Automatic Quality Assessment of Wikipedia
Articles-A Systematic Literature Review”[60]. Table 1 contains the complete list of features …

Quality Flaws Prediction in Wikipedia by Using Deep Learning Approaches

G Capodici, G Bazán Pereyra, R Bonnin… - … )(La Rioja, 3 al 6 de …, 2023‏ - sedici.unlp.edu.ar
Quality flaws prediction in Wikipedia is an ongoing research trend. In particular, in this work
we tackle the problem of automatically predicting four out of the ten most frequent quality …