Wikimedia Research Fund 2026 - Invitation for feedback - Wiki-research-l - lists.wikimedia.org

GitHub - monperrus/wikipedia-decline-llm: Estimating Wikipedia traffic decline due to AI chatbots using the Wikimedia Pageviews API

Estimating Wikipedia traffic decline due to AI chatbots using the Wikimedia Pageviews API - monperrus/wikipedia-decline-llm

Gender and intersectional bias in featured biographies on the front page of the Italian edition of Wikipedia, 2014–2024

Purpose. The purpose of this study is to examine gendered and intersectional patterns of visibility in all biographical entries featured on the Italian edition of Wikipedia Main Page (2014–2024). This paper addresses a major gap in Wikipedia research, as, to the best of the authors’ knowledge, no prior work has analysed how front-page curation in the Italian edition allocates symbolic visibility across gender, nationality, ethnicity, language or occupation.Design/methodology/approach. A decade-long data set of 4,310 front-page biographies was collected from arquivo.pt and daily captures, reconciled with Wikidata properties (gender, nationality, native language, ethnicity, religion, occupation and birth/death dates) and analysed using SQL queries, Universal Decimal Classification-based occupational aggregation and visual analytics.Findings. The results of this study show extreme and persistent gender imbalance (86% men; 0.04% non-binary/trans), strong recency bias and a pronounced Euro–North American concentration. Women are underrepresented across all periods, countries and professions; gaps peak in the Middle Ages (7.84:1) and remain high in contemporary figures (5.74:1). Public-facing occupations dominate, particularly writers, footballers and politicians. Metadata incompleteness in ethnicity, language and religion restricts deeper intersectional examination.Research limitations/implications. Incomplete sociocultural metadata constrain intersectional granularity; future work should improve Wikidata coverage and cross-edition comparisons.Practical implications. Results inform editors, policymakers and Wikimedia initiatives seeking to rebalance gender and cultural representation on high-visibility interfaces.Social implications. Front-page visibility shapes public perceptions of cultural importance; current patterns reinforce systemic inequalities and historical androcentrism.Originality/value. To the best of the authors’ knowledge, this is the first systematic, longitudinal, intersectional analysis of the Italian edition of Wikipedia Main Page. This paper conceptualises the Main Page as a socio-technical gatekeeping device and demonstrates how visibility regimes reproduce entrenched cultural and gendered hierarchies.

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