We present a method to automatically detect and identify events from social media sharing web sites. Our approach is based on the observation that many photos and videos are taken and shared when events occur. We select 9 venues across the globe that demonstrate a significant activity according to the EventMedia dataset and we thoroughly evaluate our approach against an official ground truth obtained directly by scraping the event venues' web sites. The results show our ability to not only detect events with high accuracy but also mine and identify events that have not been published in popular event directories such as Last.fm, Eventful or Upcoming. In addition to the textual identification of events, we show how we can build visual summaries of past events providing viewers with a more compelling feeling of the event's atmosphere.
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