Low-supervision urgency detection and transfer in short crisis messages
TABLE II: Details on datasets used for experiments.
['Dataset', 'Unlabeled / Labeled Messages', 'Urgent / Non-urgent Messages', 'Unique Tokens', 'Avg. Tokens / Message', 'Time Range']
For evaluating the approaches laid out in Section IV, we consider three real-world datasets described in Table II. [CONTINUE] Originally, all the raw messages for the datasets described in Table II were unlabeled, in that their urgency status was [CONTINUE] unknown. Since the Macedonia dataset only contains 205 messages, and is a small but information-dense dataset, we labeled all messages in Macedonia as urgent or non-urgent (hence, there are no unlabeled messages in Macedonia per Table II). For the two other Twitter-based datasets, we used [CONTINUE] terms of urgent and non-urgent messages. Table II shows that Nepal is roughly balanced, while Kerala is imbalanced. We