Tag: machine learning

The future of machine learning in journalism

Kevin Wall, a visual journalist at The Boston Globe, is just beginning to use machine learning in his reporting. But the large amounts of data he needs to leverage this […]

January 2, 2019April 10, 2019 Floris Wu Longform

Carlos Scheidegger on why data science needs to be done humanely

The bias inherent in machine learning algorithms and other computer systems is an issue that concerns many industries, including journalism. For example, reporters such as Julia Angwin – formerly with ProPublica […]

November 15, 2018November 15, 2018 Floris Wu Insights, Research

Accelerating knowledge: Four takeaways from an IBM data visualization expert

Northeastern University professor Mauro Martino is one of the minds behind IBM’s Watson News Explorer, a dashboard that allows users to explore the themes surfacing across the news ecosystem. Martino spoke last week […]

February 27, 2017April 26, 2017 Felippe Rodrigues Insights, Research

What is Storybench?

Storybench takes an “under the hood” look at the latest in digital storytelling, from data visualization and investigative journalism to virtual reality and the digital humanities. In addition to in-depth features and interviews with industry practitioners, we offer hands-on tutorials that can be “downloaded” right into the newsroom or classroom.

We also publish research we're running at Northeastern's School of Journalism along with collaborators in data science, communication studies, computational social sciences and information design. These projects include the Co-Laboratory for Data Impact, the Climate Journalism Lab, the 2020 Storybench Election Coverage Tracker and the Reinventing Local TV News project.

Want to contribute to Storybench? Pitch us or join us for a graduate degree in the Media Innovation program at Northeastern University’s School of Journalism.

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Storybench 2020 Election Coverage Tracker

The Storybench 2020 Election Coverage Tracker intends to keep tabs on the political coverage of the 2020 presidential election by covering media trends and using various data sources to explore media narratives.

Instead of keeping track of who’s ahead in the horse race, we’ll be turning our focus to those covering the horse race – the media outlets themselves and various proxies for public attention. Follow along here.

Best of Storybench

How the Wall Street Journal visualized 500+ conflicts of interest of the Trumps

Women on the 2020 campaign trail are being treated more negatively by the media

Getting started with data visualization in R using ggplot2

Understanding what makes a visualization memorable

Using French wine reviews to understand TF-IDF, a measure of how unique a word is to a document

Projects

Over the next two years we’ll be surveying the media’s coverage of the candidates and the issues. Follow along here.

The Reinventing Local TV News Project, from Northeastern’s School of Journalism, is analyzing the formats and practices of local news stations, and suggesting new ways of telling stories that can better engage diverse audiences. Read our inaugural post here.

The Climate Journalism Lab

The Climate Journalism Lab aims to examine and unpack the trends, tools and techniques employed by reporters and organizations covering climate change.

Join us at Northeastern!

Want to write for Storybench and probe the frontiers of media innovation? Apply for one of our graduate programs at Northeastern University’s School of Journalism.

Rolling admissions, no GREs required and financial aid available. Email here.

Interviews

Pizza, Press & Politics is our weekly speaker series at Northeastern’s School of Journalism. Watch interviews with David Filipov, Mike Workman, Jenn Smith, Martha Durkee-Neuman, Susan Labandibar, John Ward, Marc Fortier, Carol Gregory, Ling-Mei Wong and Elana Gordon.

Collaborative, Open, Mobile

Over the last three years, Storybench has interviewed 72 data journalists, web developers, interactive graphics editors, and project managers from around the world to provide an “under the hood” look at the ingredients and best practices that go into today’s most compelling digital storytelling projects.

They boil down to three key areas of emphasis: 1) highly networked, team-based collaboration; 2) an ethos of open-source sharing, both within and between newsrooms; 3) and mobile-driven story presentation. Read our paper here.