DeClarE: Debunking Fake News and False Claims using Evidence-Aware Deep Learning
Table 5: Comparison of various approaches for credibility classification on SemEval dataset.
['[BOLD] Configuration', '[BOLD] Macro Accuracy', '[BOLD] RMSE']
We use the evaluation measure proposed by the task’s organizers: macro F1-score for overall classification and Root-Mean-Square Error (RMSE) over confidence scores. We observe that DeClarE (Full) outperforms all the other approaches — thereby, re-affirming its power in harnessing external evidence.