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ZENODO
Dataset . 2025
License: CC BY SA
Data sources: ZENODO
ZENODO
Dataset . 2025
License: CC BY SA
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY SA
Data sources: Datacite
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RWFork: Russian Wikipedia Fork Edits Dataset

Authors: Trokhymovych, Mykola; Kosovan, Oleksandr;

RWFork: Russian Wikipedia Fork Edits Dataset

Abstract

Description This dataset contains the edits made by editors of the Russian Wikipedia Fork (RWFork, ruwiki.ru) to the original Russian Wikipedia articles between May and September 2023. It includes detailed textual differences between the two versions of the encyclopedia, metadata changes, and additional information such as edit summaries and embeddings. These features provide a comprehensive overview of the editorial activity and enable further analysis and processing. Keywords: RWFork, Wikipedia, content differences, knowledge manipulation, data mining, text analysis, computational social science, propaganda. Dataset Details Language: Russian Size: 33,664 rows, 17 columns (main dataset) 17,745 rows, 1 column (pages that we were not able to find, extract, or parse from RWFork) Format: CSV License: CC BY 4.0 Use Case: Text mining, knowledge manipulation detection and analysis, content moderation. Processing details: The dataset was created by comparing the wikitext of the Russian Wikipedia and RWFork articles with the same title, extracting fine-grained edits: additions, deletions, and changes to the page content (text) and metadata. Only pages with content differences were included, excluding articles that were identical between the two versions or not found in RWFork. Additional features (e.g., edit summary, embedding) were calculated using OpenAI API. Files: rwfork_changed.csv (main dataset), rwfork_columns.md (descriptions of main dataset columns), rwfork_not_found.csv (pages names that we were not able to find, extract, or parse from RWFork). Attribution The dataset was compiled from Russian Wikipedia articles and its corresponding fork. Below, we provide information about the original content's license and the template to generate the link to the original source for a given page (). For example, https://ru.wikipedia.org/wiki/Москва_(ракетный_крейсер) links to the page “Москва_(ракетный_крейсер)” in Russian Wikipedia. Wikipedia Source: https://ru.wikipedia.org/wiki/ License: CC BY-SA 4.0, GFDL RWFork Source: https://ru.ruwiki.ru/wiki/ License: CC BY-SA 4.0, GFDL Limitations: The dataset is created from community-edited content and may contain inaccuracies, vandalism, or other forms of knowledge manipulation in both versions. Potential Use Cases: Analysis and detection of russian knowledge manipulation strategies in encyclopedic content. Development of algorithms for content moderation and vandalism detection. Understanding the dynamics of forked communities and their impact on the original content. Studying the differences in editorial practices and content quality between Wikipedia and its forks. Training and evaluation language models for downstream tasks using fine-grained edit data. Please cite as: @article{rwfork, title={Characterizing Knowledge Manipulation in a Russian Wikipedia Fork}, volume={19}, url={https://ojs.aaai.org/index.php/ICWSM/article/view/35910}, DOI={10.1609/icwsm.v19i1.35910}, number={1}, journal={Proceedings of the International AAAI Conference on Web and Social Media}, author={Trokhymovych, Mykola and Kosovan, Oleksandr and Forrester, Nathan and Aragón, Pablo and Saez-Trumper, Diego and Baeza-Yates, Ricardo}, year={2025}, month={Jun.}, pages={1924-1936} }

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Keywords

knowledge manipulation, Computational Social Science, data mining, Wikipedia

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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