TY - JOUR AB - Background: Twitter updates now represent an enormous stream of information originating from a wide variety offormal and informal sources, much of which is relevant to real-world events. They can therefore be highly useful forevent detection and situational awareness applications.Results: In this paper we apply customised filtering techniques to existing bio-surveillance algorithms to detectlocalised spikes in Twitter activity, showing that these correspond to real events with a high level of confidence. Wethen develop a methodology to automatically summarise these events, both by providing the tweets which bestdescribe the event and by linking to highly relevant news articles. This news linkage is accomplished by identifyingterms occurring more frequently in the event tweets than in a baseline of activity for the area concerned, and usingthese to search for news. We apply our methods to outbreaks of illness and events strongly affecting sentiment andare able to detect events verifiable by third party sources and produce high quality summaries.Conclusions: This study demonstrates linking event detection from Twitter with relevant online news to providesituational awareness. This builds on the existing studies that focus on Twitter alone, showing that integratinginformation from multiple online sources can produce useful analysis. AU - Thapen,N AU - Simmie,D AU - Hankin,CL DO - 10.1186/s13326-016-0103-z PY - 2016/// SN - 2041-1480 TI - The early bird catches the term: combining twitter and news data for event detection and situational awareness T2 - Journal of Biomedical Semantics UR - http://dx.doi.org/10.1186/s13326-016-0103-z UR - http://hdl.handle.net/10044/1/41316 VL - 7 ER -