Finding Fires with Twitter

This paper presents a notification system to identify in near-real-time Tweets describing fire events in Australia. The system identifies fire related ‘alert words’ published on Twitter which are further processed by a classifier to determine if they correspond to an actual fire event. We describe how the classifier has been established and report preliminary results. The original notification system did not include a classifier and could not discriminate between messages unrelated to ‘real’ fire events. In the first three months of operation, the system generated 42 ‘fire’ email notifications of which 20 related to actual fires and 12 of those contained Tweets that may have been of interest to fire fighting agencies. If the classifier had been used, 21 emails would have been issued: an improvement in accuracy from 48% to 78%. However, the recall score reduced from 1 to 0.8 which is not desirable for this particular task. We propose extensions to address this short coming.