Nieman's project doesn't extend Calais--just uses it well. They say they have some homegrown analysis happening too, though they unfortunately don't specify. You'd think Nieman would consider open-sourcing its good code.
As to what the very simple service does now, though, the summary on the post does well:
— 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?
So there are some very basic bar charts and maps that are the results of these queries. The data is pretty good, though far from perfect, which @EthanZ discusses in the interview. It doesn't really help, for instance, to include the tags "united states" and "america" in the same viz as separate descriptors. Also, although I'm sure they keep the labels on the x-axis of their bar charts to themselves because it's not terrible intuitive or human-readable, it's too bad Nieman doesn't offer some description. It's really hard to compare otherwise.
Nieman's project doesn't extend Calais--just uses it well. They say they have some homegrown analysis happening too, though they unfortunately don't specify. You'd think Nieman would consider open-sourcing its good code.
As to what the very simple service does now, though, the summary on the post does well:
— 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?
So there are some very basic bar charts and maps that are the results of these queries. The data is pretty good, though far from perfect, which @EthanZ discusses in the interview. It doesn't really help, for instance, to include the tags "united states" and "america" in the same viz as separate descriptors. Also, although I'm sure they keep the labels on the x-axis of their bar charts to themselves because it's not terrible intuitive or human-readable, it's too bad Nieman doesn't offer some description. It's really hard to compare otherwise.
Smart analysis of media coverage patterns? very cool.