  Methods for detecting and summarizing emergent keywords have been extensively
studied since social media and microblogging activities have started to play an
important role in data analysis and decision making. We present a system for
monitoring emergent keywords and summarizing a document stream based on the
dynamic semantic graphs of streaming documents. We introduce the notion of
dynamic eigenvector centrality for ranking emergent keywords, and present an
algorithm for summarizing emergent events that is based on the minimum weight
set cover. We demonstrate our system with an analysis of streaming Twitter data
related to public security events.
