Abstract
We deal with shrinking the stream of tweets for scheduled events in real-time, following two steps: (i) sub-event detection, which determines if something new has occurred, and (ii) tweet selection, which picks a tweet to describe each sub-event. By comparing summaries in three languages to live reports by 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).
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