Grants:Programs/Wikimedia Research Fund/Network perspectives on collective memory processes across the Arabic and English Wikipedias

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Network perspectives on collective memory processes across the Arabic and English Wikipedias
start and end datesJuly 2023 - July 2024
budget (USD)40,000 USD
fiscal year2022-23
applicant(s)• H. Laurie Jones and Brian Keegan



H. Laurie Jones and Brian Keegan

Affiliation or grant type

University of Colorado Boulder


H. Laurie Jones and Brian Keegan

Wikimedia username(s)

H. Laurie Jones: User:Hlauriejones; Brian Keegan: User:Madcoverboy

Project title

Network perspectives on collective memory processes across the Arabic and English Wikipedias

Research proposal[edit]


Description of the proposed project, including aims and approach. Be sure to clearly state the problem, why it is important, why previous approaches (if any) have been insufficient, and your methods to address it.

Although Arabic is a major international language with 5.1% of the world using it as a first language, it is poorly represented on Wikipedia: 5,899 active users for 1.2 million articles compared to 123,291 active users for 6.5 million articles in English with a similar 5.1% first language rate. Wikipedia plays an important role in documenting events. Its decades of revision history data capture important collective memory processes about how events are described and contextualized as well as how these framing processes change over time. Prior work has compared how articles about general concepts vary across languages, but this scholarship has not focused on comparative collective memory processes about sensitive topics like conflict. Articles about contemporary conflicts are likely to be sites of especially divergent framings across languages and over time.

The 2011 Arab Spring was a historic set of protests and conflicts that brought about major social movements, toppled several governments, and led to major on-going conflicts. More than a decade after these conflicts, how are these events remembered differently across languages? This project will use a combination of within- and between-subjects designs to analyze articles about the 2011 Arab Spring primarily across English and Arabic to understand distinct collective memory processes. We will leverage several types of variance to understand these dynamics: variance over time (what’s changed between 2011 and 2023?), variance across cases (how similar are articles about different countries’ protests?), and variance across language (what’s different across language editions?) This project will use quantitative methods from natural language processing (including Arabic-specific tools), network analysis, and causal inference to analyze articles’ revision history data to measure similarity, identify hyperlink and collaborative structures, and estimate the effects of articles’ changing content and relationships over time. We hypothesize that divergent framings of conflict emerge and stabilize relatively early in articles’ histories and opportunities for changing this consensus only happen after new events bring in new editors.


  • N/A


Approximate amount requested in USD.

40,000 USD

Budget Description

Briefly describe what you expect to spend money on (specific budgets and details are not necessary at this time).

The budget would pay for one academic semester and one summer of time for the graduate research assistant (GRA) to collect and analyze data and prepare manuscripts.

1 semester GRA 50% appointment - $14,210

1 summer GRA 75% appointment - $14,036

Fringe - $3,107

Tuition + Fees - $7,370 + $800 = $8,170


Address the impact and relevance to the Wikimedia projects, including the degree to which the research will address the 2030 Wikimedia Strategic Direction and/or support the work of Wikimedia user groups, affiliates, and developer communities. If your work relates to knowledge gaps, please directly relate it to the knowledge gaps taxonomy.

Our findings comparing collective memory processes have implications for AI systems (machine translation, language models, etc.) amplifying biases, evaluating the reliability of knowledge graphs (Wikidata, etc.), and supporting the advancement of Arabic NLP literature. The project will also support Movement Strategy initiatives to bridge the gap in content and understanding between language communities by identifying topics of content disparity. Our findings will promote a connection between individual editors and multilingual users to build a trusted environment for knowledge sharing.


Plans for dissemination.

This project will implement open-source tools for working with Arabic text from Wikipedia projects and comparing content across language editions, develop reports and blog posts for the Wikipedia communities across languages documenting our findings, and publish academic manuscripts about content (dis)similarity processes in collaborative collective memory processes for social computing and computational social science audiences.

Past Contributions[edit]

Prior contributions to related academic and/or research projects and/or the Wikimedia and free culture communities. If you do not have prior experience, please explain your planned contributions.

No previous WMF funding.

Porter, E., Krafft, P.M., & Keegan, B. (2020) “Visual Narratives and Collective Memory across Peer-Produced Accounts of Contested Sociopolitical Events.” ACM Transactions on Social Computing, 3(1), 1–20.

Keegan, B. (2019). “The Dynamics of Peer-Produced Political Information During the 2016 U.S. Presidential Campaign.” ACM CSCW.

Twyman, M.,* Keegan, B., & Shaw, A. (2017). “Black Lives Matter in Wikipedia: Collaboration and Collective Memory around Online Social Movements.” ACM CSCW.

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