CLCYLGSIFeb 6, 2024

Stanceosaurus 2.0: Classifying Stance Towards Russian and Spanish Misinformation

arXiv:2402.03642v12 citationsh-index: 14WNUT
Originality Synthesis-oriented
AI Analysis

This work provides a dataset for analyzing cross-cultural misinformation in Russian and Spanish, which is incremental as it builds on an existing framework.

The authors extended the Stanceosaurus corpus to include Russian and Spanish tweets to address misinformation in these languages, achieving a macro F1 score of 43 using zero-shot cross-lingual transfer with multilingual BERT.

The Stanceosaurus corpus (Zheng et al., 2022) was designed to provide high-quality, annotated, 5-way stance data extracted from Twitter, suitable for analyzing cross-cultural and cross-lingual misinformation. In the Stanceosaurus 2.0 iteration, we extend this framework to encompass Russian and Spanish. The former is of current significance due to prevalent misinformation amid escalating tensions with the West and the violent incursion into Ukraine. The latter, meanwhile, represents an enormous community that has been largely overlooked on major social media platforms. By incorporating an additional 3,874 Spanish and Russian tweets over 41 misinformation claims, our objective is to support research focused on these issues. To demonstrate the value of this data, we employed zero-shot cross-lingual transfer on multilingual BERT, yielding results on par with the initial Stanceosaurus study with a macro F1 score of 43 for both languages. This underlines the viability of stance classification as an effective tool for identifying multicultural misinformation.

Foundations

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