Research:Newsletter/2026/February - Meta-Wiki

Nature of sources cited in German-language Wikipedia pages on German Christmas Markets

Temporal patterns of preferences through Wikipedia editing in different languages

Wikilambda the ultimate: the Wikimedia foundation’s search for the perfect language - AI & SOCIETY

In (Vrande 2020), the Wikimedia foundation launched its first new project in nearly a decade. The new project consists of two main parts: (1) Wikifunctions, a library of programming functions; and (2) Abstract Wikipedia, a language-agnostic Wikipedia that will be dynamically translated into the reader’s native tongue. Lying beneath both Wikifunctions and Abstract Wikipedia is a new system called Wikilambda, which can execute code in potentially any programming language, providing a massively flexible computing service drawing on Wikifunctions and powering Abstract Wikipedia. The entire system is designed to address a fundamental bias in Wikipedia, namely its bias towards majority languages such as English and Spanish. In this paper, I present Wikilambda as an audacious attempt to realise a ‘perfect language’, as theorised by Umberto Eco (The Search for the Perfect Language. Making of Europe. Oxford, UK Eco U (1995) The search for the perfect language. Oxford, Cambridge, Mass., USA: Blackwell) Wikilambda provides a way of specifying functions that is supposed to transcend any particular ‘native’ language. In this way, it provides editors of Wikifunctions and Abstract Wikipedia with a way of contributing to the overall system no matter which ‘native’ programming languages they know. More broadly, Wikilambda aims to achieve the ‘democratization of programming’, by enabling any person to use any function without needing to know English or a particular programming language (Vrandečić 2021). To analyse the technical and ideological aspects of Wikilambda, I apply the techniques of Critical Code Studies (Marino in Critical Code Studies, The MIT Press, Marino MC 2020) Critical code studies. The MIT Press, Cambridge. https://doi.org/10.7551/mitpress/12122.001.0001 ) to ‘the orchestrator’, the JavaScript application that instantiates Wikilambda’s new functional programming language. In the absence of a formal specification of the language, the Abstract Wikipedia team has gradually hacked Wikilambda out of JavaScript, leaving a fascinating public record of their attempt to realise their vision for a universal programming system.

Science Fiction and Fantasy in Wikipedia: Exploring Structural and Semantic Cues

Identifying which Wikipedia articles are related to science fiction, fantasy, or their hybrids is challenging because genre boundaries are porous and frequently overlap. Wikipedia nonetheless offers machine-readable structure beyond text, including categories, internal links (wikilinks), and statements if corresponding Wikidata items. However, each of these signals reflects community conventions and can be biased or incomplete. This study examines structural and semantic features of Wikipedia articles that can be used to identify content related to science fiction and fantasy (SF/F).

Thomas Davidson (@thomasdavidson.bsky.social)

Our new paper is out today in @pnasnexus.org with colleagues at Yale (@matthewshu.com, Danny Karell, @keitarookura.bsky.social) We wanted to understand how using AI-generated summaries to learn about history influenced attitudes compared to existing resources like Wikipedia. 1/4

WikiResearch (@WikiResearch) on X

RT @Res_Pol: Birkenmaier, Stroppe, Wurthmann & Sältzer use NLP+Wikidata on 50k tweets and 190k FB posts (Bundestag 2017–2021) to map geogra…

Quantifying (Mis)alignment Between Reader Focus and Editor Citation in Scholarly Biomedical Topics in Wikipedia

Abstract. When people seek health information online they often turn to Wikipedia, trusting Wikipedia’s citation of scholarly biomedical research. However, despite Wikipedia’s important role in providing health information, it is unclear how reliably this scholarly information proliferates to all biomedical topics on Wikipedia. In this paper, we quantitatively explore both (a) how scholarly biomedical research is cited in biomedically-focused Wikipedia articles, and (b) whether this reflects the topical patterns of those articles' readership in Wikipedia. Our methods identify quantitative avenues for improved alignment between editors' limited effort and readers' focus, with respect to both the biomedical topics themselves and the caliber of biomedical research cited. In other words, readers focus on topics that are very human-focused, but editors focus their citation work on basic science topics (e.g. molecular and cellular biology), leading to disproportionate citation rates of basic research publications for biomedical topics in Wikipedia. These results highlight straightforward but previously invisible design recommendations to help readers better contextualize the health information they seek on Wikipedia.