Quality Change: Norm or Exception? Measurement, Analysis and Detection of Quality Change in Wikipedia

Abstract

Wikipedia has been turned into an immensely popular crowd-sourced encyclopedia for information dissemination on numerous versatile topics in the form of subscription free content. It allows anyone to contribute so that the articles remain comprehensive and updated. For enrichment of content without compromising standards, the Wikipedia community enumerates a detailed set of guidelines, which should be followed. Based on these, articles are categorized into several quality classes by the Wikipedia editors with increasing adherence to guidelines. This quality assessment task by editors is laborious as well as demands platform expertise. As a first objective, in this paper, we study evolution of a Wikipedia article with respect to such quality scales. Our results show novel non-intuitive patterns emerging from this exploration. As a second objective we attempt to develop an automated data driven approach for the detection of the early signals influencing the quality change of articles. We posit this as a change point detection problem whereby we represent an article as a time series of consecutive revisions and encode every revision by a set of intuitive features. Finally, various change point detection algorithms are used to efficiently and accurately detect the future change points. We also perform various ablation studies to understand which group of features are most effective in identifying the change points. To the best of our knowledge, this is the first work that rigorously explores English Wikipedia article quality life cycle from the perspective of quality indicators and provides a novel unsupervised page level approach to detect quality switch, which can help in automatic content monitoring in Wikipedia thus contributing significantly to the CSCW community.

Language-Agnostic Modeling of Wikipedia Articles for Content Quality Assessment across Languages

“…All of these approaches assume the quality as a static attribute but it becomes obsolete often with the update of content. A complementary direction has been explored by (Zhang, Ren, and Kraut 2020;Das et al 2022) in which authors add temporal dimension to the static measurement of article quality and characterize the quality of articles through a number of dynamic changes in the quality states spanning over time.…”

Developing Students’ Scientific Literacy through Wikipedia Digital Library

“…The popularity of Wikipedia is due to the completeness of its topics, both in social and scientific aspects. Information spreading from Wikipedia also increases on various issues through free content [3]. The platform features explicit, novel content and easy-to-understand information [4].…”