Tracking Knowledge Propagation Across Wikipedia Languages
Keywords:Measuring predictability of real world phenomena based on social media, e.g., spanning politics, finance, and health, Centrality/influence of social media publications and authors, Trend identification and tracking; time series forecasting, Social network analysis; communities identification; expertise and authority discovery
AbstractIn 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.
How to Cite
Valentim, R. V., Comarela, G., Park, S., & Sáez-Trumper, D. (2021). Tracking Knowledge Propagation Across Wikipedia Languages. Proceedings of the International AAAI Conference on Web and Social Media, 15(1), 1046-1052. Retrieved from https://ojs.aaai.org/index.php/ICWSM/article/view/18128