Robust clustering of languages across Wikipedia growth

TL;DR

This study analyzes the growth patterns of 26 Wikipedia language editions over 15 years, revealing six robust clusters that are independent of language families and influenced by cultural and informational factors.

Contribution

The paper introduces a robust clustering approach to identify growth patterns across Wikipedia languages, independent of traditional language family classifications.

Findings

Six well-defined clusters of Wikipedias with shared growth patterns

Clusters are consistent across four different clustering methods

Growth factors are linked to cultural and informational similarities, not language families

Abstract

Wikipedia is the largest existing knowledge repository that is growing on a genuine crowdsourcing support. While the English Wikipedia is the most extensive and the most researched one with over five million articles, comparatively little is known about the behavior and growth of the remaining 283 smaller Wikipedias, the smallest of which, Afar, has only one article. Here we use a subset of this data, consisting of 14962 different articles, each of which exists in 26 different languages, from Arabic to Ukrainian. We study the growth of Wikipedias in these languages over a time span of 15 years. We show that, while an average article follows a random path from one language to another, there exist six well-defined clusters of Wikipedias that share common growth patterns. The make-up of these clusters is remarkably robust against the method used for their determination, as we verify via four different clustering methods. Interestingly, the identified Wikipedia clusters have little correlation with language families and groups. Rather, the growth of Wikipedia across different languages is governed by different factors, ranging from similarities in culture to information literacy.