Transformation of Communication Processes: Data Journalism

Data journalism can be mistaken as the new buzzword for infographics. This is true, but only to some extent. Visualizing data to tell stories started long before the Internet came into being. What makes an attractive infographics, is not the great design, but, more importantly, the insight it gives. The John Snow’s map of cholera outbreaks from nineteenth century London, is an example of reference. The English physician mapped the cases of cholera deaths in the Soho district of London. Back then, the very notion of germs did not exist. Being mapped, the plain data gave an insight: the outliers clustered around the pump. This is just one of many examples of maps and charts that give another perspective on the same dataset. Another important part of data journalism – or, more precisely, data-driven journalism, is the use of computers, math and statistical analysis. Computer-assisted reporting was born in the American newsroom in the late 1960s, where technological advances met the social sciences. It was during the US national elections in 1952 when journalists first used a computer to predict the outcome of the vote – and the machine got it right. Fifteen years later Philip Meyer, a journalist working at the Detroit Free Press, used IBM 360 to cover the Detroit riots in 1967. Through a machine survey, he was able to investigate the dataset and sketch a profile of the rioters. This Pulitzer-winning story was the first attempt by a journalist to use analytical methods from sociology, behavioral science research methods and similar domains in the context of a newsroom. Philip Meyer himself called this “precision journalism.” The increasing size of datasets was another step on the way to data-driven journalism. In 2006, Adrian Holovaty, an American web developer, journalist and entrepreneur, wrote a blogpost which turned out to be a manifesto for data-driven journalism.1 His main point was that “newspapers need to stop the story-centric