Low-supervision urgency detection and transfer in short crisis messages
TABLE IV: Results investigating RQ1 on the Nepal and Kerala datasets. (a) Nepal
['System', 'Accuracy', 'Precision', 'Recall', 'F-Measure']
Table IV illustrate the result for RQ1 on the Nepal and Kerala datasets. The results illustrate the viability of urgency detection in low-supervision settings (with our approach yielding 69.44% F-Measure on Nepal, at 99% significance compared to the Local baseline), with different feature sets contributing differently to the four metrics. While the local embedding model can reduce precision, for example, it can help the system to improve and accuracy and recall. Similarly, manual features reduce recall, but help the system to improve accuracy and precision (sometimes considerably).