Last week, Harvard’s Berkman Center for Internet & Society launched Media Cloud, an intriguing tool that could help researches and others understand how stories spread through mainstream media and blogs.
According to Nieman Lab, “Media Cloud is a massive data set of news — compiled from newspapers, other established news organizations, and blogs — and a set of tools for analyzing those data.
Here’s what Berkman’s Ethan Zuckerman had to say about Media Cloud:
Some of the kinds of questions Media Cloud could eventually help answer:
- How do specific stories evolve over time? What path do they take when they travel among blogs, newspapers, cable TV, or other sources?
- What specific story topics won’t you hear about in [News Source X], at least compared to its competitors?
- When [News Source Y] writes about Sarah Palin [or Pakistan, or school vouchers], what’s the context of their discussion? What are the words and phrases they surround that topic with?”
The obvious use of this project is to compare coverage by different types of media. But I think a deeper purpose may be served here: By tracking patterns of words used in news stories and blog posts, Media Cloud may illuminate how context and influence shape public understanding — in other words, how media and news affect people and communities.
This is important, because news and media do not exist for their own sake. It seems to me that the more we learn about how people are affected by — and affect — media, the better we’ll be able to craft effective media for the future.
(NOTE: I originally published this article in Poynter’s E-Media Tidbits.)