On the Assessment of Information Quality in Spanish Wikipedia

Abstract

Featured Articles (FA) are considered to be the best articles that Wikipedia has to offer and in the last years, researchers have found interesting to analyze whether and how they can be distinguished from “ordinary” articles. Likewise, identifying what issues have to be enhanced or fixed in ordinary articles in order to improve their quality is a recent key research trend. Most of the approaches developed in these research trends have been proposed for the English Wikipedia. However, few efforts have been accomplished in Spanish Wikipedia, despite being Spanish, one of the most spoken languages in the world by native speakers. In this respect, we present a first breakdown of Spanish Wikipedia’s quality flaw structure. Besides, we carry out a study to automatically assess information quality in Spanish Wikipedia, where FA identification is evaluated as a binary classification task. The results obtained show that FA identification can be performed with an F1 score of 0.81, using a document model consisting of only twenty six features and AdaBoosted C4.5 decision trees as classification algorithm.