Unsupervised and Interpretable Domain Adaptation to Rapidly Filter Social Web Data for Emergency Services
Table 5. Crisis Tweet Classification Results: Comparison of Single-Task versus Multi-Task models.
['TARGET', '[BOLD] Priority Single-Task', '[BOLD] Priority Single-Task', '[BOLD] Priority Multi-Task', '[BOLD] Priority Multi-Task', '[BOLD] Factoid Single-Task', '[BOLD] Factoid Single-Task', '[BOLD] Factoid Multi-Task', '[BOLD] Factoid Multi-Task']
The results show clear performance improvement for Priority, Factoid, and Irrelevant tasks. However, Sentiment task did not show significant improvement. We speculate that this is because other tasks do not generalize the bottom layer enough to boost the sentiment classification performance. These results show the usefulness of multi-tasking where different tasks help each other when the data is sparse and labels are limited.