On Sept. 30 and Oct. 1, 2016 we hosted the Computation + Journalism Symposium at Stanford. The annual conference explored the interface between journalism and computing.

Previous years:

We host Hacks/Hackers events at Stanford to bring journalists ("hacks") and technologists ("hackers") from the Stanford and wider Silicon Valley communities together.


We've been exploring criminal justice data, transportation data, governmental corruption and campaign finance activity in politics. But it's just the beginning.

Big Local News
Big Local News is a program of Stanford University’s Journalism and Democracy Initiative and collects local data to discover the regional or national patterns that will yield stories with impact.
California Civic Data Coalition
A team from the Los Angeles Times Data Desk, the San Francisco Chronicle, The Center for Investigative Reporting and the Stanford Computational Journalism Lab.
Corruption Conference
An exploration of defining and measuring corruption in politics as seen through the lens of legal scholarship, journalism and political science.
Data Driven, Coding and Writing Transportation's Future
A conference focused on the changing landscape of vehicle and transportation-related data, and the opportunities arising from it.
Stanford Open Policing Project
The Stanford Open Policing Project (formerly known as Law, Order & Algorithms project) is continuing to collect, clean and analyze more than 100 million records of police interactions data, including traffic stops across American highways.
Peninsula Press news website
Peninsula Press is the Stanford Journalism Program's data-driven, multimedia wesbite where student reporters report on the communities across Silicon Valley and the greater Bay Area.
Stanford Journalism and Democracy Initiative
Stanford University is uniquely positioned to help journalists hold democratic institutions accountable and improve the flow of reliable information to the public. Those are core goals of the new Stanford Journalism and Democracy Initiative.
Immersive Storytelling
Establishing best practices and ideal scenarios for using 360-degree video and virtual reality technology in immersive storytelling.


We're teaching classes in the Stanford Journalism Program focused on public affairs, computational methods, investigative reporting and immersive storytelling.

Students across Stanford can enroll in data-focused journalism classes that explore storytelling with data, investigative reporting and technical tools to gather, analyze and present data for news audiences.

Interested in joining our master's program in journalism? The Stanford Journalism Program admissions page has more information.

Public Affairs Data Journalism I
We study the methods, and the data, used to discover leads and conduct in-depth reporting on public affairs, including election finance and safety regulations. Students gain practical experience with the digital tools and techniques of computer-assisted reporting.
Exploring Computational Journalism
This project-based course will explore the field of computational journalism, including the use of Data Science, Info Visualization, AI, and emerging technologies to help journalists discover and tell stories, understand their audience, advance free speech, and build trust
BigLocal Journalism - A Project-Based Class
This class tackles data-driven journalism, in collaboration with other academic and journalistic partners. The class is centered around one or more projects rooted in local data-driven journalism but with potential for regional or national journalistic stories and impact.
Public Affairs Data Journalism II
Learn how to find, create and analyze data to tell news stories with public service impact. Uses relational databases, advanced queries, basic statistics and mapping to analyze data for storytelling. Assignments may include stories, blog posts and data visualizations, with at least one in-depth project based on data analysis.
Programming in Journalism
Students gain basic proficiency in the Unix shell and Python programming while practicing skills such as web scraping, acquiring data from public APIs, cleaning and transforming data, and working with spreadsheets and databases.
Virtual Reality Journalism in the Public Sphere
The immersive space (cinematic VR and virtual reality) is journalism's newest and most exciting reporting and storytelling tool. We survey best practices and methods in this emerging medium and learn 360-degree video production and postproduction. Teams will illuminate issues and provoke conversation in the public sphere.
Investigative Watchdog Reporting
Learn how to apply an investigative and data mindset to journalism, from understanding how to background an individual or entity using online databases to compiling or combining disparate sets of information in ways that unveil wrongdoing or mismanagement. Focuses on mining texts, tracking associations and using visualizations. Stories produced apply investigative techniques to beat reporting, breaking news and long-form journalism.
Building News Applications
Students will study examples from the news industry and gain proficiency in a range of technical languages, skills and tools including version control, HTML, CSS, Javascript, Python, web protocols, and web hosting and deployment.


Resources to get your feet wet in data analysis and reporting.

An assignment for the Computational Journalism class: 101 real world web scraping exercises in Python 3 for data journalists
Data Exploration with OpenRefine
How to use OpenRefine as a power tool for cleaning and exploring data.
Clustering text facets in OpenRefine
OpenRefine gives point-and-click access to a variety of powerful text clustering algorithms.
A little Tableau tutorial
A quick tutorial of Tableau and visualizing Washington state lobbying expenditures.
Getting Started with SQLite and Sequel Pro
An introduction to using SQL with a GUI client
Mapping Census data using Arcmap with ESRI
Tips to easily map Census data.
Busting data out of PDFs
A walkthrough of software and methods for extracting textual data from PDFs.



Democracy's Detectives

In a new book, Jay Hamilton writes about how 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.

Learn more

Teaching Data and Computational Journalism Report

Cheryl Phillips co-authored the "Teaching Data and Computational Journalism" report, published by Columbia Journalism School and The Knight Foundation. This 88-page book covers the history of data journalism, a survey of data journalism education in higher education today and models for integrating data journalism education into journalism and communication departments. Since the publication of the report, co-author Charles Berret and Phillips have spoken at a variety of conferences in in smaller groups with education leaders to help set the path forward for journalism schools in terms of teaching data journalism.

Read the report

Tech Team Report

After 10 weeks of experimenting with a myriad of data tools in Cheryl Phillips' "Becoming a Watchdog: Investigative Reporting Techniques" Spring 2015 course (co-taught with Stanford Engineering Professor Bill Behrman and director of Stanford’s Data Lab), students on the class' technology team wrote up their experience as a guide for others. The guide covers everything from web scraping to mapping and data visualization, with pros, cons and opinions on how easy each program or software package is to use. It shares the experiences of the class as they worked through their projects.

Read the report