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This content is part of the Essential Guide: Guide to telling stories with data: How to share analytics insights
Definition

data journalism

Contributor(s): Ed Burns

Data journalism in an approach to writing for the public in which the journalist analyzes large data sets to identify potential news stories. 

Journalists who work in this field typically make use of sophisticated statistical analysis techniques, such as a regression analyses as well as programs that incorporate machine learning to spot meaningful correlations in data. Nate Silver helped popularize data journalism in 2012 when he correctly predicted results in the presidential election for all 50 states and the District of Columbia while blogging for The New York Times. His predictions were based on statistical analyses of past polling data, which he used to develop predictive models. Since his success, other journalists have tried to make data analysis a larger part of their reporting. Proponents say data journalism enables reporters to dig deeper into investigations and identify stories that they otherwise might have missed. Opportunities for journalists to perform data analyses are increasing, with the United States federal government and companies like Twitter making large data streams available to the public.

This was last updated in September 2014

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