WikiGap: Promoting Epistemic Equity by Surfacing Knowledge Gaps Between English Wikipedia and other Language Editions

2025-05-30

AI Summary

English Wikipedia’s epistemic hegemony leads readers to overlook culturally contextual, complementary facts available in other language editions. This paper proposes a user-centered approach to enhance cross-lingual knowledge visibility: by jointly performing multilingual information-gap mining and cross-lingual entity alignment, it identifies critical factual omissions in the French, Russian, and Chinese Wikipedias relative to the English edition, and dynamically surfaces these gaps as real-time annotations via a browser extension integrated into the English interface. To our knowledge, this is the first system enabling dynamic visualization of non-English complementary knowledge on a mainstream Wikimedia platform. A mixed-methods evaluation demonstrates statistically significant improvements: fact retrieval accuracy increases, task completion time decreases markedly, and usability scores rise by 32 points; users’ perception of English Wikipedia’s factual completeness also shifts substantially. The work advances multilingual knowledge equity and cognitive decentralization.

Technology Category

• Data Mining & Knowledge Management: Knowledge Acquisition from the Web
• Natural Language Processing: Fact-Checking / Misinformation Detection (NLP Focus)
• Knowledge Representation and Reasoning: Knowledge Representation Languages

Application Category

• Web Mining and Content Analysis: Mining multimedia, multimodal, multilingual, cross-lingual Web data
• Search and Retrieval-Augmented AI: Multilingual and cross-lingual Web search
• Semantics and Knowledge: Representation, semantic annotation, enhancement, enrichments, access and/or integration of a variety of data on the Web

Abstract

With more than 11 times as many pageviews as the next, English Wikipedia dominates global knowledge access relative to other language editions. Readers are prone to assuming English Wikipedia as a superset of all language editions, leading many to prefer it even when their primary language is not English. Other language editions, however, comprise complementary facts rooted in their respective cultures and media environments, which are marginalized in English Wikipedia. While Wikipedia's user interface enables switching between language editions through its Interlanguage Link (ILL) system, it does not reveal to readers that other language editions contain valuable, complementary information. We present WikiGap, a system that surfaces complementary facts sourced from other Wikipedias within the English Wikipedia interface. Specifically, by combining a recent multilingual information-gap discovery method with a user-centered design, WikiGap enables access to complementary information from French, Russian, and Chinese Wikipedia. In a mixed-methods study (n=21), WikiGap significantly improved fact-finding accuracy, reduced task time, and received a 32-point higher usability score relative to Wikipedia's current ILL-based navigation system. Participants reported increased awareness of the availability of complementary information in non-English editions and reconsidered the completeness of English Wikipedia. WikiGap thus paves the way for improved epistemic equity across language editions.

Problem

• Addressing knowledge gaps between English and non-English Wikipedia editions
• Enhancing access to complementary cultural facts in non-English Wikipedias
• Improving epistemic equity by surfacing multilingual information gaps

Innovation

• Multilingual information-gap discovery method
• User-centered design for interface
• Surfaces complementary facts cross-language