• by Mark Walsh  @markfwal, March 11, 2009

Thomson Reuters has partnered with Harvard University's Berkman Center for Internet & Society to launch the Media Cloud, a set of research tools for tracking online media coverage.

The joint effort is meant to bring some clarity to the vast tangle of news and information on the Web, attempting to answer questions about what types of stories are covered by which media sources, where stories begin, and how blogosphere coverage compares to that of the mainstream media.

The open-source project will debut in the second quarter of 2009.

"While daily newspapers struggle for survival, political, niche and special interest blogs continue to thrive," said Yochai Benkler, faculty co-director of the Berkman Center, in a statement. "In the midst of this upheaval, it is difficult to know where stories begin, who sets the agenda, and how these dramatic changes impact news coverage on the whole."

Media Cloud will comprise an ever-growing archive of news stories and blog posts that have been analyzed using Thomson Reuters' Calais Web service. It a automatically tags relevant people, places, companies, facts and events to facilitate research into how media sources relate to each other.

Users will be able to this data to generate charts and other graphics showing, for instance, how sources cluster or diverge, where new news stories come from, and what new media flows are emerging. A sample "visualization" uses world maps to compare how heavily three news outlets -- The New York Times, the BBC and TalkingPointsMemo -- cover individual countries.

Media Cloud stemmed from a debate between Benkler and Berkman Fellow Ethan Zuckerman over whether the blogosphere mainly echoed traditional media or was instead a source of original news and agenda-setting.

"So we wanted it to settle the arguments we have around here, but what we really want to do is make it possible for anyone who's studying media to do so in a rigorous quantitative way without doing any of the scut work of actually collecting these huge sets of data, cleaning them up, and doing the topic classification," said Zuckerman in an interview on the site of Harvard's Nieman Journalism Lab.