We present a novel topic modelling-based methodology to track emerging events in microblogs such as Twitter. Our topic model has an in-built update mechanism based on time slices and implements a dynamic vocabulary. We first show that the method is robust in detecting events using a range of datasets with injected novel events, and then demonstrate its application in identifying trending topics in Twitter.
Lau et al. REF developed a method to track emerging events on Twitter using a topic model based on time slices and a dynamic vocabulary.
On-line Trend Analysis with Topic Models: \#twitter Trends Detection Topic Model Online
COLING
Computer Science