WSDMS: Debunk Fake News via Weakly Supervised Detection of Misinforming Sentences with Contextualized Social Wisdom (2023.emnlp-main)
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| Challenge: | Existing methods for debunking fake news rely on blending of authentic and fabricated content by creators. |
| Approach: | They propose a model that detects misinformation at sentence-level using social media conversations . they use a bag-level annotation system to train the model . |
| Outcome: | The proposed model outperforms existing state-of-the-art models on three real-world benchmarks and outperformed existing state of the art models in debunking fake news at sentence and article levels. |
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