What is Computational Journalism?

Computational journalism is an evolving field. Definitions include:

“What is computational journalism? Ultimately, interactions among journalists, software developers, computer scientists and other scholars over the next few years will have to answer that question. For now though, we define computational journalism as the combination of algorithms, data, and knowledge from the social sciences to supplement the accountability function of journalism.”

James T. Hamilton and Fred Turner, “Accountability through Algorithm: Developing the Field of Computational Journalism” (a report from Developing the Field of Computational Journalism, a Center for Advanced Study in the Behavioral Sciences Summer Workshop, July 27–31, 2009), 2.

Computational journalism, “Broadly defined ... can involve changing how stories are discovered, presented, aggregated, monetized, and archived.”

Sarah Cohen, James T. Hamilton, and Fred Turner, “Computational Journalism,” Communications of the ACM 54 (2011): 66

In analyzing the dimensions of computation that could advance sense making in journalism, Terry Flew and coauthors note: “Automation alleviates activities such as data gathering and interpretation, number crunching, network analysis, sorting, and processing that would otherwise need to be done manually; algorithms allow operators to follow predefined steps needed to accomplish certain goals, identify problems, find suitable solutions in a large set of alternatives, and verify information in a reliable, consistent and efficient manner; and abstraction enables the qualification of different levels or perspectives from which an idea may be presented or new directions that may be explored.”

Terry Flew, Christina Spurgeon, Anna Daniel, and Adam Swift , “The Promise of Computational Journalism,” Journalism Practice 6 (2012): 159

Though computational journalism builds on and incorporates elements of computer-assisted reporting and data journalism, this new approach often involves larger data sets and more sophisticated algorithms. Recent advances in computational journalism center on reporting by algorithms, about algorithms, and through algorithms. Stories generated by computer algorithms include those by Narrative Science and Automated Insights, companies seen as leaders in “Automation in the Newsroom.” The Wall Street Journal and ProPublica have each done reporting that looks at the disparate impacts of private and government algorithms on different groups in society. Reporters are also using algorithms to mine for stories, as the Atlanta Journal Constitution did in using web scraping and machine learning to identify potential cases across the country of doctors involved in sexual misconduct. The papers and video (to come) from the 2016 Computation + Journalism conference at Stanford show recent computational advances in story discovery, telling, and distribution.

About the Class

Tuesdays/Thursdays, 10:30 a.m. - 11:50 a.m.

Chaffee Seminar Room (Rm. 452), McClatchy Hall (Bldg. 120)

This course will explore the evolving field of computational journalism. Students will research and discuss the state of field in five areas where computation is affecting journalism:


AI, Data Science, and Info Viz


Emerging Hardware Tech, including Drones, Sensors and VR


Audience Participation and Diverse Viewpoints


Free Speech and Democracy


News Ecosystem and Business Models

Admission to the course is by application. The fifteen students in the course will be divided into five teams of three students. Each team will work on describing the state of the art in CS research and journalism practice on a narrow question within the track. Each team will help select readings for discussion about their track, lead a session on that track, help the class converge on the narrow question to pursue in that track, and develop a final paper (15 pages maximum) and final presentation (3-5 minutes) which captures what is possible and probable in the overlap of computation and journalism they are examining.

Timeline:

  • WEEK ONE (Jan. 10 and Jan. 12): Intro - How can you discover and tell stories through computational journalism?

  • WEEK TWO (Jan 17. and Jan. 19): Team Formation and Problem Definition

  • WEEK THREE (Jan. 24 and Jan. 26): AI, Data Science and Info Viz

  • WEEK FOUR (Jan. 31 and Feb. 2): Emerging Hardware Tech: Drones, Sensors and VR

  • WEEK FIVE (Feb. 7 and Feb. 9): Audience Participation and Diverse Viewpoints

  • WEEK SIX (Feb. 14 and Feb. 16): Free Speech and Democracy

  • WEEK SEVEN (Feb. 21 and Feb. 23): News Ecosystem and Business Models

  • WEEK EIGHT (Feb. 28 and March 2): Project presentations, Tracks 1 and 2

  • WEEK NINE (March 7 and March 9): Project presentations, Tracks 3 and 4

  • WEEK TEN: Project presentation Track 5 (March 14) and final presentations (March 16)

Application for COMM 281/CS 206

Thank you for your interest in COMM 281/CS 206, Exploring Computational Journalism. Please copy the questions below into the text of an email, complete your responses and email to Professor Jay Hamilton at jayth@stanford.edu.

First priority applications are due Nov. 18, 2016, however we'll accept applications beyond that deadline, depending on available space. The instructors will be reviewing applications with an eye toward selecting a collection of 15 students with backgrounds that will enable the seminar participants to delve into the five research areas.

1.) In this course, students will research and discuss the state of field in five areas where computation is affecting journalism: AI, Data Science and Info Viz; Emerging Hardware Tech, including Drones, Sensors and VR; Audience Participation and Diverse Viewpoints; Free Speech and Democracy; and News Ecosystem and Business Models. Which of these areas would you be most interested in exploring? Why?

2.) Can you describe previous experiences and interests you've had in journalism and/or CS that have led you to be interested in computational journalism?

3.) Is there anything else you would like us to know about why you would like to take the class?