We focus on:

 

How can we use data and algorithms to lower the costs of discovering stories?

How do we tell stories in more personalized and engaging ways?


We are:

 

Journalists, academics and computer scientists -- all part of the interdisciplinary ecosystem of journalism innovation at Stanford.

Learn more about us

We are working on:

 

Pioneering a data-focused curriculum

We have launched five new Stanford courses focused on public affairs reporting, computational methods and investigative journalism. We're also exploring immersive storytelling with virtual reality and 360-degree video in a new class.

Decoding campaign finance data

We are helping the California Civic Data Coalition make the state's arcane database tracking money in politics easy to mine -- a project awarded $250,000 by Knight Foundation.  
 

Building a data journalism community

We host Hacks/Hackers meetups at Stanford and are hosting the 2016 Computation + Journalism Symposium at Stanford this year.  
 
 
 


Investigating American traffic stop data

The Law, Order & Algorithms project at Stanford is continuing to collect, clean and analyze more than 100 million records of police interactions data, including traffic stops across American highways.

Exploring immersive storytelling

We are establishing best practices and ideal scenarios for using 360-degree video and virtual reality technology in immersive storytelling.  
 

Publishing a library of data tutorials

We are adding more and more free, online resources to get your feet wet in data analysis and reporting.  
 
 
 


See more initiatives

Introducing "Democracy's Detectives":

 

Investigative journalism is underprovided in the market, but new combinations of data and algorithms may make it easier for journalists to discover and tell the stories that hold institutions accountable.

DEMOCRACY'S DETECTIVES: The Economics of Investigative Journalism
By James T. Hamilton

Investigative journalism involves original work, about substantive issues, that someone wants to keep secret. This means it is costly, underprovided in the marketplace, and often opposed. It gets done when a media outlet has the resources to cover the costs, has an incentive to tell a new story, cares about impacts, and overcomes obstacles. Changes in media markets have put local investigative reporting particularly at risk. But new combinations of data and algorithms may make it easier for journalists to discover and tell the stories that hold institutions accountable.

CJ Lab co-founder Jay Hamilton writes all about this in his new book, published Fall 2016.

Learn more about the book

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