The ElectionWatch site demonstrates the application of modern machine learning and language technologies to the analysis of political discourse in news relative to the US Presidential Elections 2012.
It is updated daily, by presenting narrative patterns as they were extracted from news. Narrative patterns include actors, triplets representing political support between actors, and automatically inferred political allegiance of actors. Furthermore, it presents the key named entities, timelines and heat maps. Network analysis allows us to infer the role of each actor in the general political discourse, recognising adversaries and allied actors. Users can browse articles by political statements, rather than by keywords. For example, they can browse articles where Romney is described as criticising Obama. All the graphical briefing is automatically generated and interactive: each relation presented to the user can be used to retrieve supporting articles, from a set of hundreds of online news sources.
The research being showcased is led by Professor Nello Cristianini of the Intelligent Systems Laboratory at the University of Bristol, and performed by Saatviga Sudhahar, Thomas Lansdall-Welfare, Ilias Flaounas. The group is part of the European Union's Pattern Analysis, Statistical Modelling and Computational Learning (PASCAL) Network of Excellence funded under the European Commission's Information Society Technologies (IST) programme.