# A Weibo Dataset for the 2022 Russo-Ukrainian Crisis

arXiv: https://arxiv.org/abs/2203.05967 · HTML: https://mlsanity.com/paper/2203.05967/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 19 references that are in the map.
- First posted on arXiv 9 Mar 2022.

## Builds on (most cited first, 3 of 3)

- [Hierarchical Propagation Networks for Fake News Detection: Investigation and Exploitation](https://mlsanity.com/paper/1903.09196/) (2019)
- [Twitter Dataset for 2022 Russo-Ukrainian Crisis](https://mlsanity.com/paper/2203.02955/) (2022)
- [Mitigation of Diachronic Bias in Fake News Detection Dataset](https://mlsanity.com/paper/2108.12601/) (2021)

## Built on by (most cited first, 2 of 2)

- [PropaInsight: Toward Deeper Understanding of Propaganda in Terms of Techniques, Appeals, and Intent](https://mlsanity.com/paper/2409.18997/) (2024)
- [Massively Multi-Lingual Event Understanding: Extraction, Visualization, and Search](https://mlsanity.com/paper/2305.10561/) (2023)

## 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.