  This paper explores the real-time summarization of scheduled events such as
soccer games from torrential flows of Twitter streams. We propose and evaluate
an approach that substantially shrinks the stream of tweets in real-time, and
consists of two steps: (i) sub-event detection, which determines if something
new has occurred, and (ii) tweet selection, which picks a representative tweet
to describe each sub-event. We compare the summaries generated in three
languages for all the soccer games in "Copa America 2011" to reference live
reports offered by Yahoo! Sports journalists. We show that simple text analysis
methods which do not involve external knowledge lead to summaries that cover
84% of the sub-events on average, and 100% of key types of sub-events (such as
goals in soccer). Our approach should be straightforwardly applicable to other
kinds of scheduled events such as other sports, award ceremonies, keynote
talks, TV shows, etc.
