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Stanford and Columbia students awarded 'Magic Grants' to bring innovation to the media world

By Bjorn Carey

The Magic Grant program aims to encourage and support new endeavors with the potential to inform and entertain in transformative ways. (Photo: Shutterstock)

The Brown Institute for Media Innovation has awarded seed funding to teams of students, post-docs and faculty from Stanford and Columbia universities to develop new technologies that could transform the ways media content is produced, delivered and consumed.

The winning projects include a natural language processor that detects media bias, an experiment in augmenting stories with virtual reality and a suite of machine learning tools to study redaction patterns in declassified documents.

The annual "Magic Grants" were made possible by a $30 million endowment gift from longtime Cosmopolitan magazine editor and author Helen Gurley Brown to establish the David and Helen Gurley Brown Institute for Media Innovation, a partnership between Stanford University's School of Engineering and Columbia University's Graduate School of Journalism.

The institute – and the collaboration between the two schools – is designed to promote Brown's wish to embrace the increasingly important connection between journalism and technology. The Magic Grant program, in particular, aims to encourage and support new endeavors with the potential to inform and entertain in transformative ways, and bring together the best from the East and West coasts.

"David and Helen Gurley Brown believed that giving uncomplicated grants to students to realize their ideas is a wonderful way to encourage new media technologies and the creation of innovative contents," said Bernd Girod, director of the Brown Institute at Stanford and a professor in the School of Engineering.

"If you look beyond the Brown Institute, there are not many programs with this same scale and focus," Girod said. "Journalism needs to reinvent itself. Digital distribution has disrupted the industry in significant ways. No one knows what the journalism landscape will look like in 10 years. The Magic Grants allow Stanford and Columbia students to experiment and try new ideas that could really change how journalism is done."

“This year, we gave special priority to projects that led with a story,” said Mark Hansen, director of the Brown Institute at Columbia and professor in the Graduate School of Journalism. “Often journalists and storytellers take a back seat when it comes to technology. This year, we looked for stories that didn’t fit comfortably in existing publication frameworks, but instead required new kinds of tools.”

At Stanford, a review committee composed of two computer science faculty members, a journalist and a venture capitalist scored each proposal on four criteria: novelty, intellectual merit, potential impact and quality of the team. Reviewers also placed a strong emphasis on the ability to execute on an idea and demonstrate products or prototypes, with an ultimate aim to bring the innovations to market.

Three groups of students from Stanford were selected to receive full funding – up to $100,000 – to develop their projects over the next year. A fourth group received partial funding to purchase equipment and conduct user testing, and will receive additional funds from the Max Planck Center for Visual Computing and Communication.

Following are the winning Stanford projects:

Gistraker: A collaboration by Richard Socher and Rebecca Weiss, Gistraker is a Web application that analyzes the sentiment of language used in news media. Users will be able to create filters and explore visual summaries of how different media outlets cover specific actors or issues of interest, which could reveal instances of media bias.

Ensemble: Ensemble is a Web platform created by Joy Kim and Justin Cheng that provides structure to collaborative storytelling. In Ensemble, one person is assigned the responsibility of managing creative direction, and can then enlist a crowd of friends or strangers to perform various tasks – such as contributing narrative direction or developing a character's back story – with an ultimate goal of creating more engaging stories by drawing from the different personal viewpoints and experiences of a group.

Widescope: Developed by Pranav Dandekar and David Lee, Widescope is an online social media platform designed to crowd-source federal and state budget proposals to drive greater consensus on budgets and budget deficits. Users can design a budget – for example, proposing greater funding for education and less for defense, or vice versa – and then interact with other users to restructure various proposals to arrive at a single consensus.

Storytelling with Augmented Reality (STAR): A project proposed by Hao Su, Matt Yu, Roland Angst and Peter Vajda, STAR will experiment with using augmented reality software on mobile devices in combination with location- and viewpoint-aware storytelling. The group hopes to foster more interactive and immersive storytelling by displaying a video stream of virtual content that overlaps with live images of the physical world as viewed on a mobile device.

At Columbia, Hansen convened a review team consisting of computer science and journalism faculty as well as New York-based technology writers and data journalists.  Four grants were awarded:  two received $150,000, with half of the funding coming from the Tow Center for Digital Journalism and the other two grantees will receive up to $100,000.

Following are the Magic Grant recipients awarded by Columbia:

CityBeat: A collaboration between The New York World housed in Columbia Journalism School, and the Social Media Information Lab at Rutgers University, this project will look for newsworthy events in the patterns of real-time, geotagged social media feeds. (Half of this project’s budget will come from the Tow Center.)

The Declassification Engine: A partnership between faculty and students in the Departments of History, Statistics and Computer Science at Columbia University, this project will probe the limits of official secrecy by applying natural language processing software to archives of declassified documents to examine whether it is possible to predict the contents of redacted text; attribute authorship to anonymous documents; and model the geographic and temporal patterns of diplomatic communications. (Half of this project’s budget will come from the Tow Center.)

NewsHub: A team of graduate students and recent graduates of the Columbia School of Journalism and the School of Engineering and Applied Science will create a system for tracking censorship in authoritarian regimes post-publication, i.e., when a story is revised or deleted after publication. The team will create real-time assessments and monthly reports of journalistic improprieties around the globe.

Bushwig: A Columbia School of Journalism documentary film student and a PhD candidate in the Rutgers University School of Communication and Information will tell the story of a drag renaissance taking place in Bushwick, Brooklyn, that is enlisting and extending social media platforms for the “identity curation” that happens in the drag community.

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