Unsupervised Fact Checking by Counter-Weighted Positive and Negative Evidential Paths in A Knowledge Graph (2020.coling-main)
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| Challenge: | Misinformation spreads across media, community, and knowledge graphs in the Web by human agents and information extraction algorithms. |
| Approach: | They propose a rule-based approach that finds positive and negative evidential paths in a knowledge graph for a given factual statement and calculates a truth score for the given statement by unsupervised ensemble. |
| Outcome: | The proposed approach outperforms the state-of-the-art unsupervised approaches by up to 0.12 AUC-ROC and even outperfies the supervised approach by up 0.05 AUC. |
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