More than one million news articles in 22 languages have been analysed using the latest technology to pinpoint the factors that influence and shape the news agenda in 27 European countries.
Every day hundreds of news outlets across Europe choose which story to cover from a wide and diverse selection. While each outlet may make news choices based on individual criteria, clear patterns emerge when these choices are studied across many outlets and over a long period of time.
They discovered that chosen news content 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 European Union later.
Professor Lewis said: “This approach has the potential to revolutionise the way we understand our media and information systems. It opens up the possibility of analysing the mediasphere on a global scale, using huge samples that traditional analytical techniques simply couldn’t countenance. It also allows us to use automated means to identify clusters and patterns of content, allowing us to reach a new level of objectivity in our analysis.”
Professor Cristianini, University of Bristol added: “Automating the analysis of news content could have significant applications, due to the central role played by the news media in providing the information that people use to make sense of the world.”
(via European news agenda – cardiff.ac.uk/news)
Sadly though, there is no elaboration on exactly which shared interests countries have, and exactly what kind of issues outlying countries are more interested in. (Most likely, news about non-EU countries’ that share their other borders.)
The big potential use I can see for all of this is the automated discovery of potential stories of interest – a feed of ‘stories my local media are not reporting’. It would be interesting to see if the same techniques could work for the entire news output of a single country, so we could get an analysis of stories across the UK.
It seems the researchers really went above and beyond what should be possible for their study…
[…] the team was able to analyse 1,370,874 articles – a sample size well beyond existing research techniques.