Abstract
The goal of Event extraction is to extract structured information of events that are of interest from unstructured documents. Existing event extractors for social media suffer from two major problems: lack of context and informal nature. In this paper, instead of conducting event extraction solely on each social media message, we incorporate cross-genre knowledge to boost the event extractor performance. Experiment results demonstrate that without any additional annotations, our proposed approach is able to provide 15% absolute F-score improvement over the state-of-the-art.