Organisation: FiveThirtyEight (United States)
Publication Date: 04/10/2017
Size of team/newsroom:large
DescriptionFiveThirtyEight is the most prominent data journalism site in the U.S., and its third year since relaunching in 2014 was by far its most successful. The staff tackled more ambitious stories with higher stakes; it deepened its analysis in politics, policy, sports and science. We covered the biggest political story in a generation -- the election of Donald Trump -- as well as anyone; as a result of our reporting and modeling, we came closer to understanding how Trump won than almost any other media outlet. And most significantly, we have increasingly married statistical analysis with shoe-leather and investigative reporting. We’ve never believed this was an either-or proposition; using the best tools journalism has to offer, no matter what they are, produces the best stories. Data journalism is simply good journalism.
What makes this project innovative? What was its impact?More than 150 million people visited FiveThirtyEight in 2016. And most of those people left our web site better informed on the significant issues of the day. That, ultimately, is our goal. At a time when fake news competes with partisan news competes with opinion journalism, FiveThirtyEight provided readers with sober, humble and accurate reporting and analysis. The site is making the world smarter … probably.
Technologies used for this project:We use a wide variety of technologies for our work at FiveThirtyEight. For data analysis we mostly use R but we also use Python, Ruby, STATA and Excel. For interactive visualizations we use D3 and Node.js. For static visualizations, we often use D3 or ggplot2 with Illustrator as well as some internal web-based tools we built using Node.js and React. For databases and backend interfaces we often use Ruby on Rails with MySQL or Postgres. For mapping we mostly use QGIS. We have many different bots that help us with our work by keeping track of different data sources. They communicate with our various databases and predictive models and interact with our journalists via Slack. We use GitHub to publish the data and source code behind our work.
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