mlsanityData to 7 Oct 2026

A Weibo Dataset for the 2022 Russo-Ukrainian Crisis

arXiv 2203.05967 ↗First posted 9 Mar 2022cs.SI cs.CLcited by 2

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Abstract (arXiv)

Online social networks such as Twitter and Weibo play an important role in how people stay informed and exchange reactions. Each crisis encompasses a new opportunity to study the portability of models for various tasks (e.g., information extraction, complex event understanding, misinformation detection, etc.), due to differences in domain, entities, and event types. We present the Russia-Ukraine Crisis Weibo (RUW) dataset, with over 3.5M user posts and comments in the first release. Our data is available at https://github.com/yrf1/RussiaUkraine_weibo_dataset.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 3 of its 19 references that are in the map. First posted on arXiv 9 Mar 2022.

Builds on

3 of 19 references.

References · 3

  1. 2019Hierarchical Propagation Networks for Fake News Detection: Investigation and Exploitationcited by 32
  2. 2022Twitter Dataset for 2022 Russo-Ukrainian Crisiscited by 6
  3. 2021Mitigation of Diachronic Bias in Fake News Detection Datasetcited by 5

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Cited by year

Citing papers per year: 2023: 1; 2024: 1.

2 papers.

  1. 2024PropaInsight: Toward Deeper Understanding of Propaganda in Terms of Techniques, Appeals, and Intentcited by 9
  2. 2023Massively Multi-Lingual Event Understanding: Extraction, Visualization, and Searchcited by 5