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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?


闪光测速- 爬墙专用加速器

 

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

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闪光测速- 爬墙专用加速器

 
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Pioneering a data-focused curriculum

We launched 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.

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Collecting and archiving local data

We go after data sets that are hard to obtain because they’re kept in disparate, scattered locations by multiple jurisdictions. Big Local News collects local data to discover the regional or national patterns that will yield stories with impact.  
 

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Building a data journalism community

We host Hacks/Hackers meetups at Stanford and hosted the 2016 Computation + Journalism Symposium at Stanford.  
 
 
 


Investigating American traffic stop data

We are part of the Stanford Open Policing Project, gathering, analyzing, and releasing records from millions of traffic stops by law enforcement agencies across the country.

Exploring immersive storytelling

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

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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.  
 
 
 


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闪光测速- 爬墙专用加速器

 

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

闪光测速- 爬墙专用加速器

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