“I updated the <ref>”: The evolution of references in the English Wikipedia and the implications for altmetrics

Abstract

With this work, we present a publicly available dataset of the history of all the references (more than 55 million) ever used in the English Wikipedia until June 2019. We have applied a new method for identifying and monitoring references in Wikipedia, so that for each reference we can provide data about associated actions: creation, modifications, deletions, and reinsertions. The high accuracy of this method and the resulting dataset was confirmed via a comprehensive crowdworker labelling campaign. We use the dataset to study the temporal evolution of Wikipedia references as well as users’ editing behaviour. We find evidence of a mostly productive and continuous effort to improve the quality of references: (1) there is a persistent increase of reference and document identifiers (DOI, PubMedID, PMC, ISBN, ISSN, ArXiv ID), and (2) most of the reference curation work is done by registered humans (not bots or anonymous editors). We conclude that the evolution of Wikipedia references, including the dynamics of the community processes that tend to them should be leveraged in the design of relevance indexes for altmetrics, and our dataset can be pivotal for such an effort. Peer Review https://publons.com/publon/10.1162/qss_a_00171

From academic to media capital: To what extent does the scientific reputation of universities translate into Wikipedia attention?

“…Wikipedia is used frequently in altmetrics studies (Colavizza, 2020; Nielsen, 2007; Yang & Colavizza, 2022). There are numerous reference‐based studies exploring the coverage and characteristics of publications cited in Wikipedia (Kousha & Thelwall, 2017; Lewoniewski et al, 2017; Nicholson et al, 2021; Teplitskiy et al, 2017; Torres‐Salinas et al, 2018), and several works collect these citations which are used to generate and publish datasets (Singh et al, 2020; Zagorova et al, 2022), or adapt classical scientometrics techniques such as co‐citation networks (Arroyo‐Machado et al, 2020; Didegah & Thelwall, 2018). Some authors such as Maggio et al (2020) study engagement patterns.…”