Discovery in the data: Stanford's data journalism program advances the storytelling form

Stanford's data journalism program blends the power of big data with journalistic training in the craft of storytelling. Students and faculty are crossing disciplines to enhance the way news stories are told in the digital age.

Bill Behrman teaching journalism class

Bill Behrman, second from right, director of the Stanford Data Lab, works with students in a data journalism class. (Image credit: L.A. Cicero)

In an increasingly digital world, information can be expressed in incredible ways. That is a key lesson students learn quickly in the Stanford Journalism Program, a graduate-level field of study that involves analyzing data – lots of data – and crafting stories that make a difference in people’s lives.

By analyzing and filtering large data sets, Stanford students and faculty are diving deeper into issues than technology has ever allowed. But while numbers may be the catalyst, the students recognize that they are just the start of what resonates in hearts and minds.

Digital news

Carolina Wilson, a 2015 graduate of the program, took a new “digital” approach to the issue of bike commuter traffic in the San Francisco Bay Area. Her story, which combined a written narrative, high-resolution photography, video, and data visualized on custom map graphics, came together in a digital news package that was published in local newspapers.

“Attending Stanford’s program in journalism was the best decision I could have made for my career in news,” said Wilson, who won the 2015 Student Edward R. Murrow Award for her story and is now a reporter at Bloomberg News in New York City. “I was not only trained in news judgment and writing, in the power of video and photography, and with the essential tool of working with and visualizing data, but above all else, I learned how to be a storyteller.”

Like others in the program, Wilson learned how to mesh multiple tools including text, video and data visualization, said Jay Hamilton, the director of the Stanford Journalism Program.

“Her use of data to discover and tell a story about public policy is exactly the type of journalism we hope to support in our coursework at Stanford,” he said.

Students cultivate those skills in courses and places like the Stanford Computational Journalism Lab, which according to Hamilton is concerned with two questions: “How can you lower the cost of discovering stories? And how can you tell stories in more personalized and engaging ways?”

Recent highlights include launching five new courses on public affairs reporting, computational methods and investigative journalism; exploring immersive storytelling with virtual reality in a new seminar; assisting the California Civic Data Coalition to track money in politics; and organizing speaker events, such as Hacks/Hackers conference and a likely hosting of the Computation + Journalism Symposium in 2016.

Student Jeff Barrera found the program transformative – and flexible, as it cuts across academic disciplines.

“I’m learning to collect and analyze data, connect public policy debates to people’s lives, and tell stories through writing, data graphics and multimedia,” said Barrera, who expects to graduate next year.

To undertake his project on bike crashes, Barrera learned web skills in the journalism program, statistical analysis in political science courses, and algorithm design in computer science classes.

‘Becoming a watchdog’

Cheryl Phillips, an award-winning former journalist with The Seattle Times, is a lecturer in the Communication Department where last spring she helped launch the Stanford Computational Journalism Lab. She also taught a data-focused investigative reporting course – “becoming a watchdog” – along with Bill Behrman, director of the Stanford Data Lab in the Institute for Computational and Mathematical Engineering.

Cheryl Phillips teaching journalism

Lecturer Cheryl Phillips teaches Stanford students how to use data analysis for investigative reporting. (Image credit: L.A. Cicero)

In that class, students were drawn from both computer science and journalism programs. They worked on watchdog projects – “shorter-term, tightly focused journalism that tended to have an investigatory nature,” as Phillips described it.

For example, one team investigated the historical record of a Redwood City recycling plant that had been fined by the Environmental Protection Agency and another worked with the Center for Investigative Reporting to build a first-time and wholly original interactive map of child-care centers that featured up-to-date inspection records.

Another group of students, Phillips said, examined the money and social media efforts behind the right-to-die effort, and other students studied eviction patterns in San Francisco.

“The journalism members were tasked with learning the basics of data journalism and continuing to hone their investigative reporting skills,” she said.

The tech team produced a report that will soon be published by Investigative Reporters and Editors as a resource for people who work in the field of data journalism.

This spring, Phillips’ class will work on campaign finance data with the California Civic Data Coalition. “Some of the students in the spring will use the data to find and tell important campaign finance stories,” she said. “Other students may work with data we have been collecting and analyzing in collaboration with another professor on campus on state patrol stops and searches.”

When possible, the goal is to publish this Stanford student work in news outlets, she added.

Phillips said that with the print newspaper industry’s decline, computational journalism can help provide cost-efficient tools and resources.

“By using computational methods – think algorithms and machine-learning – we can lower the cost of important journalism and surface patterns and outliers for journalists to identify and report upon,” she said.

‘Exponentially faster’

Dan Nguyen, a leading developer in the field of data journalism and a communication lecturer at Stanford, said the “computational” part of computational journalism acknowledges that news research and reporting needs to scale with big data and information now available. In news, time and resources are limiting factors, but data filtering can help immensely on both fronts.

“If the use of a computer can make such fact-finding and research exponentially faster, then it should be a no-brainer to think of the bigger picture for any given story,” Nguyen said.

He noted that Barrera, who took one of his classes, generated a year’s worth of California Highway Patrol data on vehicle accidents involving cyclists and built a site that not only shows the incidents on a map but also shows how the data compare across various jurisdictions. As a result, the story is told more deeply and broadly than a typical news piece focusing on individual accidents would allow, Nguyen said.

Other student successes include Austin Meyer, who won a New York Times competition to take a trip with columnist Nicholas Kristof; Farida Jhabvala Romero, who now works at KQED and who saw her project on suspended licenses featured by KQED; and Allison McCartney, who won a Magic Grant to analyze defense contracting data.

Stanford is also home to the David and Helen Gurley Brown Institute for media innovation, a collaboration between Stanford and Columbia universities to support new endeavors in media innovation.