An information gap exists across Wikipedia’s language editions, with a considerable proportion of articles available in only a few languages. As an illustration, it has been observed that 10 languages possess half of the available Wikipedia articles, despite the existence of 330 Wikipedia language editions. To address this issue, this study presents an approach to identify the information gap between the different language editions of Wikipedia. The proposed approach employs Latent Dirichlet Allocation (LDA) to analyze linked entities in a cross-lingual knowledge graph in order to determine topic distributions for Wikipedia articles in 28 languages. The distance between paired articles across language editions is then calculated. The potential applications of the proposed algorithm to detecting sources of information disparity in Wikipedia are discussed, and directions for future research are put forward.
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Detecting Cross-Lingual Information Gaps in Wikipedia
Semantic Scholar · Computer Science · 2023
Abstract
An information gap exists across Wikipedia’s language editions, with a considerable proportion of articles available in only a few languages. As an illustration, it has been observed that 10 languages possess half of the available Wikipedia articles, despite the existence of 330 Wikipedia language editions. To address this issue, this study presents an approach to identify the information gap between the different language editions of Wikipedia. The proposed approach employs Latent Dirichlet Allocation (LDA) to analyze linked entities in a cross-lingual knowledge graph in order to determine topic distributions for Wikipedia articles in 28 languages. The distance between paired articles across language editions is then calculated. The potential applications of the proposed algorithm to detecting sources of information disparity in Wikipedia are discussed, and directions for future research are put forward.