By Asma Ghribi
If you’ve been reading the news every day for the last five years, as I have been doing, there’s no doubt that you’ve noticed many changes in the articles you’ve been reading. Most of them use more technology.
We’ve seen articles incorporating Tweets and other social media, articles based around ‘listicles’ made popular on websites like Buzzfeed, other articles embedding video and audio. The list goes on. However, many of these changes are simply adaptations to the Internet, more than innovation.
One new use of technology in media that is, for me, truly innovative: data journalism.
‘Data journalism’ is still a somewhat recent term. It refers to reporting that draws its conclusions from analyzing a large set of data, not from traditional sources such as interviews and documents. It can be as simple as taking data that’s already widely available, from the census or politicians’ financial disclosure forms, and presenting it in such a way that allows readers to see patterns and gain a better understanding of what is happening around them.
Often, data journalism makes use of charts, maps, or other graphic ways of presenting data that make trends and exceptions visually clear.
The information is aggregated and simplified in such a way that mountains of numbers become pieces of news: obesity levels are lower in cities; poverty is deepest in the south; and other interesting findings.
While these conclusions could be written, the images grab attention and make the patterns strikingly clear — even to readers who might not normally spend time on dry, statistics-based articles. Even better, recent software makes it relatively easy to make such graphics interactive, allowing the readers to explore the data themselves to better grasp the different findings.
But the use of data journalism does not only help present numbers in a way that’s clear and engaging: its use can help reporters break stories.
By analyzing raw data, journalists, particularly those with some training in statistics, can discover a story where no one else saw one. In a recent example, the Guardian analyzed data from the International Whaling Commission and found that the most common collisions between boats and whales were caused by whale-watching boats.
The story will come as a shock to many tourists who think of whale watching as a way to appreciate nature — and will not please businesses that make money from such trips.
The New York Times and others have similarly broken stories from their analysis of information that revealed many troubling conclusions.
Data journalism is something I would like to explore more as I gain more experience and training.
In my fellowship at the Wall Street Journal, I’ve gotten my first taste.
Recently, I was assigned to work with the “Numbers” blog. We work with reports from non-profits, government agencies, and others, and briefly point out the most interesting findings. Our mission is pretty clearly explained in its motto: “The Wall Street Journal examines the way numbers are used and abused.”
I love the motto because it points out the paradox of basing your reporting around statistics.
On one hand, numbers are hard and reliable. Events, words, and images are easy to twist and manipulate.
Numbers are cold, hard facts.
On the other hand, numbers rely on people to interpret them and give them significance.
The most basic task for journalists working with numbers is to make sure they understand how the numbers were gathered and how the terms were defined.
For instance, does ‘middle class’ refer to those who make an average income or a median income?
Most importantly, journalists have to be sure that the numbers they are conveying were not gathered in a biased way to make them suit any agenda.