Extracting topics based on authors, recipients and content in microblogs
Nazneen Fatema Rajani, Kate McArdle, Jason Baldridge · 2014
Microblogs such as Twitter are important sources for spreading vital information at high speed. They also reflect the general people's reaction and opinion towards major events or stories. With information traveling so quickly, it is helpful to be able to apply unsupervised learning techniques to discover topics for information extraction and analysis. Although graphical models have been traditionally used for topic discovery in microblogs and text streams, previous work may not be as efficient because of the diverse and noisy nature of microblogs.