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This resource page features course content from the Knight Center for Journalism in the America's massive open online course (MOOC) titled "News Algorithms: The Impact of Automation and AI on Journalism." The four-week course took place from February 11 to March 10, 2019. We are now making the content free and available to students who took the course and anyone else who is interested in the impact of automation and AI on journalism.


The course, which was supported by the Knight Foundation, was taught by Nicholas Diakopoulos. He created and curated the content for the course, which includes video classes, readings, exercises, and more.


The course materials are broken up into four modules:

  • Module 1: Provides a broad overview of how algorithmic approaches are being used in journalism, including areas like content production and computational story discovery.
  • Module 2: Provides a lot more detail on automated content production, including how it works and is used by news organizations, as well as covering its benefits and limitations so you know when it might be appropriate to deploy. The instructor will demonstrate the basics for how to write a template using a tool called Arria Studio, which is a word processor for creating your own automated content.
  • Module 3: Covers algorithms in news curation and dissemination, like at Google, Facebook, and Apple News, which use algorithms in different ways to drive exposure to content. It also covers how to think about metrics and how editorial criteria can be encoded into the curation algorithms that your own news organization might be developing.
  • Module 4: Covers how algorithms are creating a new object for journalistic investigation, which is giving rise to a specialized practice called algorithmic accountability reporting. The instructor will detail what methods you can use to investigate algorithms on this beat, and how you can be more responsible with the algorithms you might incorporate into your newswork.

As you review this resource page, we encourage you to watch the videos, review the readings, and complete the exercises as time allows. The course materials build off each other, but the videos and readings also act as standalone resources that you can return to over time.


We hope you enjoy the materials. If you have any questions, please contact us at knightcenter@austin.utexas.edu.



About the Instructor



Nicholas Diakopoulos is an Assistant Professor in Communication Studies and Computer Science (by courtesy) at Northwestern University where he is Director of the Computational Journalism Lab (CJL). He is also a Tow Fellow at Columbia University School of Journalism as well as Associate Professor II at the University of Bergen Department of Information Science and Media Studies. He received his Ph.D. in Computer Science from the School of Interactive Computing at Georgia Tech where he co-founded the program in Computational Journalism. His research is in computational and data journalism with active research projects on (1) algorithmic accountability and transparency, (2) automation and algorithms in news production, and (3) social media in news contexts. He is the author of Automating the News: How Algorithms are Rewriting the Media from Harvard University Press, and the co-editor of Data-Driven Storytelling, from CRC Press. For some of his latest thinking and writing on automation and algorithms in journalism see his column in the Columbia Journalism Review.





Algorithmic News Media


This module provides a broad overview of how algorithmic approaches are being used in journalism, including areas like content production and computational story discovery.


This module will cover:

  • What algorithms are and how they’re used in news production
  • How data mining can help monitor for and discover news stories
  • How to apply computational thinking in your work

Video Class

1. An overview of algorithmic news media

Watch Video Transcript

2. Computational story discovery

Watch Video Transcript

3. Computational thinking

Watch Video Transcript

4. (Optional) News Algorithm guest speaker Pablo Martín Fernández from Chequeado

Watch Video



Readings


1. The era of news algorithms (Introduction chapter from instructor Nick Diakopoulos' book, "Automating the News: How Algorithms Are Rewriting the Media.")

2. What can machine learning do? Workforce implications [Science Magazine]

3. An algorithmic nose for news [Columbia Journalism Review]



Optional Materials






Automated Content Production


Module 2 provides a lot more detail on automated content production, including how it works and is used by news organizations, as well as covering its benefits and limitations so you know when it might be appropriate to deploy. The instructor will demonstrate the basics for how to write a template using a tool called Arria Studio, which is a word processor for creating your own automated content.


This module will cover:

  • How automated content works and is used by news organizations
  • What the benefits and limitations of automated content are for news production
  • How to write a template to drive automated text production

Video Class

1. Automated content production

Watch Video Transcript

2. Benefits & limitations of automated content

Watch Video Transcript

3. News Algorithm guest speaker Carl-Gustav Lindén, Media Journalism Researcher

Watch Video Transcript

4.(Optional) Arria Studio introduction

Watch Video Transcript

Resources for Arria Studio

4.1 Arria Studio interface

4.2 Data for Arria demo (.csv file)


Readings






Algorithms in News Curation & Dissemination


Module 3 covers algorithms in news curation and dissemination, like at Google, Facebook, and Apple News, which use algorithms in different ways to drive exposure to content. It also covers how to think about metrics and how editorial criteria can be encoded into the curation algorithms that your own news organization might be developing.


This module will cover:

  • The role and power of platform curation algorithms in news distribution
  • Approaches to content optimization and how to think about metrics for content optimization

  • Video Class

    1. Platform power & algorithmic content curation

    Watch Video Transcript

    2. Content optimization & metrics

    Watch Video Transcript

    3. News Algorithm guest speaker Tamar Charney, NPR

    Watch Video Transcript


    Readings

    1. Digital paperboys: algorithms in news distribution (Chapter 5 from instructor Nick Diakopoulos' book, "Automating the News: How Algorithms Are Rewriting the Media.")






    Algorithmic Accountability & Transparency


    Module 4 covers how algorithms are creating a new object for journalistic investigation, which is giving rise to a specialized practice called algorithmic accountability reporting. The instructor will detail what methods you can use to investigate algorithms on this beat, and how you can be more responsible with the algorithms you might incorporate into your newswork.


    This module will cover:

  • Why investigating algorithms in society is important for journalism
  • How to approach investigation of algorithms using different methods
  • How to be transparent with your own use of algorithms in newswork

  • Video Class

    1. The algorithms beat

    Watch Video Transcript

    2. Algorithmic accountability reporting methods

    Watch Video Transcript

    3. Editorial responsibility & algorithmic transparency

    Watch Video Transcript

    4. News Algorithm guest speaker Christina Elmer, Der Spiegel

    Watch Video Transcript


    Readings