A Framework to analyze the information quality of user generated content [abstract]

Abstract

User Generated Content (UGC) is growing in significance for information sharing along with the introduction of Web 2.0. Being one of the largest UGC databases in the world, Wikipedia also stands as the largest community-based collaborative encyclopedia ever created. However Wikipedia's open-source and collaborative structure presents a serious information quality (IQ) concern. Therefore, in this study a novel theoretical framework for evaluating IQ is presented, based on Google's EA-T framework. The model comprises three IQ constructs Expertise, Authority and Trustworthiness. A collection of IQ dimensions that affect the aforementioned three IQ constructs as well as 45 IQ attributes to assess the IQ dimensions were identified and presented based on empirical findings and study results. The data study employed a sample of 2000 articles from six WikiProjects, including 1000 Featured Articles (FA) and 1000 non-FA articles. The proposed model's classification and clustering accuracies were compared to those of three previously published models in terms of classification and clustering accuracy. It received classification and clustering accuracies of 95% and 93% respectively, which is a drastic improvement over the existing models. Furthermore, an average inter-rater agreement of 84% was observed. Accordingly, this comprehensive experiment fairly validates the effectiveness of the suggested model. This study contributes to the related knowledge area by introducing a novel framework to assess Wikipedia articles’ IQ.