Research Fellows Directory
Professor Nello Cristianini
University of Bristol
Computer scientists have analysed over a million news articles in 22 languages to pinpoint what factors, such as the Eurovision song contest, influence and shape the news agenda in 27 EU countries. This is the first large-scale content-analysis of cross-linguistic text using artificial intelligence techniques.
Every day hundreds of news outlets across Europe choose which story to cover from a wide and diverse selection. While each outlet may be making these choices based on individual criteria, clear patterns emerge when all these choices are studied over a large set of outlets and a long time.
The international team of researchers is led by Nello Cristianini, Professor of Artificial Intelligence at the University of Bristol in conjunction with Professor Justin Lewis, Head of the School of Journalism, Media and Cultural Studies at Cardiff University. An article published in the issue of PLoS ONE (Dec. 2010), has discovered that the news content chosen reflects national biases, as well as cultural, economic and geographic links between countries. For example outlets from countries that trade a lot with each other and are in the Eurozone are more likely to cover the same stories, as are countries that vote for each other in the Eurovision song contest.
Deviation from “normal content” is more pronounced in outlets of countries that do not share the Euro, or have joined the EU later. The analysis the researchers have conducted could not have been done in the past, due to the sheer scale of the data, but is now possible using automated methods from artificial intelligence because of recent advances in machine translation and text analysis.