Tracking Knowledge Propagation Across Wikipedia Languages

TL;DR

This paper introduces a comprehensive dataset tracking the propagation of Wikipedia concepts across 309 languages, enabling large-scale analysis of knowledge flow and structural factors influencing content spread.

Contribution

It provides the first large-scale dataset of inter-language Wikipedia knowledge propagation, aligning articles conceptually across languages and offering insights into propagation patterns.

Findings

Long cascades are rare but tend to continue after four editions.

Propagation speed correlates with the size of language editions.

The dataset enables new research on Wikipedia growth and related applications.

Abstract

In this paper, we present a dataset of inter-language knowledge propagation in Wikipedia. Covering the entire 309 language editions and 33M articles, the dataset aims to track the full propagation history of Wikipedia concepts, and allow follow up research on building predictive models of them. For this purpose, we align all the Wikipedia articles in a language-agnostic manner according to the concept they cover, which results in 13M propagation instances. To the best of our knowledge, this dataset is the first to explore the full inter-language propagation at a large scale. Together with the dataset, a holistic overview of the propagation and key insights about the underlying structural factors are provided to aid future research. For example, we find that although long cascades are unusual, the propagation tends to continue further once it reaches more than four language editions. We also find that the size of language editions is associated with the speed of propagation. We believe the dataset not only contributes to the prior literature on Wikipedia growth but also enables new use cases such as edit recommendation for addressing knowledge gaps, detection of disinformation, and cultural relationship analysis.