Cross-Language Evolution of Divergent Collective Memory Around the Arab Spring

TL;DR

This study analyzes how collective memory around the 2011 Arab Spring evolves differently in English and Arabic Wikipedia from 2011 to 2024. It operationalizes four memory-analytic constructs—salience, deliberation, contextualization, and consolidation—using longitudinal size and outlinks, temporally clustered outlink vectors, inter-language links, and country/event ego-networks. The findings reveal language-specific memory dynamics, with the English article showing greater salience, deliberation, and cross-language contextualization than the Arabic article, highlighting cross-cultural biases in online memory formation. These results inform theories of online collective memory and have practical implications for multilingual data used in training language models, emphasizing the need to account for cross-language biases and unequal representation across Wikipedias.

Abstract

The Arab Spring was a historic set of protests beginning in 2011 that toppled governments and led to major conflicts. Collective memories of events like these can vary significantly across social contexts in response to political, cultural, and linguistic factors. While Wikipedia plays an important role in documenting both historic and current events, little attention has been given to how Wikipedia articles, created in the aftermath of major events, continue to evolve over years or decades. Using the archived content of Arab Spring-related topics across the Arabic and English Wikipedias between 2011 and 2024, we define and evaluate multilingual measures of event salience, deliberation, contextualization, and consolidation of collective memory surrounding the Arab Spring. Our findings about the temporal evolution of the Wikipedia articles' content similarity across languages has implications for theorizing about online collective memory processes and evaluating linguistic models trained on these data.

Figures (7)

• Figure 1: Changes in the size (left) and number of outlinks (right) for the "Arab Spring" article in English and Arabic used to operationalize salience of the article through time.
• Figure 2: This is a figure breaking down the outlink temporal inclusion vectorization and clustering process. Beginning by identifying outlinks on each revision of the Wikipedia article and then a one hot encoding of the outlink inclusion in the English or Arabic Arab Spring articles, this results in a clustered heatmap, revealing groups of outlink that are later identified with stable, debated, and forgotten patterns
• Figure 3: English outlink similarities.
• Figure 4: Arabic outlink similarities.
• Figure 5: Outlinks as they evolve through time in English(left) and Arabic(right) categorized by whether their current outlink has an ILL in the other language version of the article, and whether it is included in that other language version.This is an operationalization of the access and application of shared contextualization practices