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ELECTIONWATCH: Online tool can detect patterns in US election news coverage
Intelligent Systems Laboratory - University of Bristol
The US presidential election dominates the global media every four years, with news articles, which are carefully analysed by commentators and campaign strategists, playing a major role in shaping voter opinion. Academics have developed an online tool, Election Watch, which analyses the content of news about the US election by the international media.
A paper about the project by academics at the University of Bristol’s Intelligent Systems Laboratory will be presented at the Internet, Politics, Policy 2012: Big Data, Big Challenges? conference held in Oxford.
The web tool allows users to explore news stories via an interactive interface and demonstrates the application of modern machine learning and language technologies. After analysing news articles about the 2012 US election the researchers have found patterns in the political narrative.
The online site is updated daily, by presenting narrative patterns as they were extracted from news. Narrative patterns include actors, actions, triplets representing political support between actors, and automatically inferred political allegiance of actors.
The site also presents the key named entities, timelines and heat maps. Network analysis allows the researchers 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, users can browse articles where Romney is described as criticising Obama. All the graphical briefing is automatically generated and interactive and each relation presented to the user can be used to retrieve supporting articles, from a set of hundreds of online news sources.
The researchers aim was to access information that is closer to what a human analyst could extract, but still simple enough to be reliably extracted by computational means in a Big Data setting.
The domain of US politics is particularly amenable to this type of network analysis, due to the binary nature of the choice (at least after the primary phase), so that all various issues and players need to ultimately fit into a bi-polar playing field. Also the communication is easily analysed, with explicit support or opposition often being stated for the candidates by various actors.
Another outcome of this study is Word Clouds of actions between actors in the Elections.
As experimental results the researchers will present at the conference both experiments on the past five election cycles, and up-to-date analysis of the 2012 election. The first set will only be based on the New York Times coverage, while the analysis of the current election will be based on more than 719 international outlets, having generated to date more than 70,000 articles. So far the researchers system has extracted 4,80,952 triplets, which contain 34,636 distinct actors. The online tool has in the in the meantime reached the mark of 1,48,104 articles.
The researchers will concentrate on two classes of results: the properties of the network of political support among actors, which reveals complex party allegiances, and the embedding of actors in a space that reveals their position in the media narrative, subjects or object of positive or negative statements.
The computational infrastructure is capable of detecting election-related articles, analysing their content, solving co-reference and anaphora, identifying verbs that denote support or opposition, identifying key actors, filtering information that is statistically not reliable, and finally analysing the properties of the resulting relational network.
While each step of the extraction phase may be imperfect, the statistical corrections coming from the use of very big datasets deliver a sufficiently clean signal for political observers to monitor the state of play of a complex process such as a US presidential campaign.
REFERENCE: Saatviga Sudhahar, Thomas Lansdall-Welfare, Ilias Flaounas and Nello Cristianini. ElectionWatch: Detecting Patterns In News Coverage of US Elections. In Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics, 2012
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DEMO SITE: http://electionwatch.enm.bris.ac.uk
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