Summary of Stanceosaurus 2.0: Classifying Stance Towards Russian and Spanish Misinformation, by Anton Lavrouk et al.
Stanceosaurus 2.0: Classifying Stance Towards Russian and Spanish Misinformation
by Anton Lavrouk, Ian Ligon, Tarek Naous, Jonathan Zheng, Alan Ritter, Wei Xu
First submitted to arxiv on: 6 Feb 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Computers and Society (cs.CY); Machine Learning (cs.LG); Social and Information Networks (cs.SI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The new iteration of the Stanceosaurus corpus, a dataset designed to combat misinformation on Twitter, has been expanded to include Russian and Spanish tweets. The dataset is significant because it addresses prevalent misinformation issues in these languages, particularly in Russia amid global tensions. By adding 3,874 tweets from Russia and Spain, researchers can now analyze multicultural misinformation more effectively. To demonstrate the value of this data, the authors used multilingual BERT for zero-shot cross-lingual transfer, achieving results comparable to the initial Stanceosaurus study with a macro F1 score of 43 for both languages. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The Stanceosaurus corpus helps researchers identify misinformation on Twitter by providing high-quality, annotated tweets. This dataset is important because it includes Russian and Spanish tweets, which are often overlooked on social media platforms. The new version has even more data to help researchers study multicultural misinformation. By using a special AI model called multilingual BERT, the authors showed that their approach can identify misinformation effectively in both languages. |
Keywords
* Artificial intelligence * Bert * F1 score * Zero shot
