Breaking news, before it breaks
Scoop detects and tracks breaking news in real-time using social media posts to break news before it hits mainstream media.
Developed over the past 7 years as part of research at the University of Glasgow, Scoop makes used a range of technologies, from Natural Language Processing and machine learning, to detect and track real-world events as they happen from social media posts, often before they are reported by the mainstream media.
Scoop is able to detect breaking news in real-time without being told what to look for, without any human interaction, and with high accuracy. This allows time and resources to be better spent acting on the information, rather than trying to find it.
Scoop has applications in a number of areas. The technology was originally developed with the aim of helping journalists discover and report breaking news faster than they could ever before, however, more recently it has been developed with the aim of providing alerts to traders about potentially market moving news. Scoop also has clear applications for security applications, where the detection and tracking of major events, such as natal disasters or terrorist attacks can allow for faster responses and better intelligence gathering.