Background: Every day, around 400 million tweets are sent worldwide, which has become a rich source for detecting, monitoring and analysing news stories and special (disaster) events. Existing research within this field follows key words attributed to an event, monitoring temporal changes in word usage. However, this method requires prior knowledge of the event in order to know which words to follow, and does not guarantee that the words chosen will be the most appropriate to monitor.
It may also require prior experience of the event to select the appropriate words to track REF .
Event Detection using Twitter: A Spatio-Temporal Approach
PLoS ONE
PLoS ONE
Computer Science Medicine