Analysing Timelines of National Histories across Wikipedia Editions: A Comparative Computational Approach
Anna Samoilenko, Florian Lemmerich, Katrin Weller, Maria Zens, and Markus Strohmaier

TL;DR
This paper introduces a computational method to compare national history timelines across Wikipedia language editions, revealing biases towards recent events and Eurocentric perspectives, and analyzing interlingual differences.
Contribution
It presents a novel approach to automatically identify and quantify biases and differences in national history narratives across multiple Wikipedia editions.
Findings
Histories are skewed towards recent events (recency bias).
European countries' histories are disproportionately emphasized (Eurocentric bias).
High interlingual consensus exists despite variations.
Abstract
Portrayals of history are never complete, and each description inherently exhibits a specific viewpoint and emphasis. In this paper, we aim to automatically identify such differences by computing timelines and detecting temporal focal points of written history across languages on Wikipedia. In particular, we study articles related to the history of all UN member states and compare them in 30 language editions. We develop a computational approach that allows to identify focal points quantitatively, and find that Wikipedia narratives about national histories (i) are skewed towards more recent events (recency bias) and (ii) are distributed unevenly across the continents with significant focus on the history of European countries (Eurocentric bias). We also establish that national historical timelines vary across language editions, although average interlingual consensus is rather high. We…
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Taxonomy
TopicsWikis in Education and Collaboration · Natural Language Processing Techniques · Topic Modeling
