Towards Open Domain Event Extraction from Twitter: REVEALing Entity Relations.

In the past years social media services received content contributions from millions of users, making them a fruitful source for data analysis. In this paper we present a novel approach for mining Twitter data in order to extract factual information concerning trending events. Our approach is based on relation extraction between named entities, such as people, organizations and locations. The experiments and the obtained results suggest that relation extraction can help in extracting events in social media, when combined with pre and post-processing steps.