Steve Rubel posted about the Audible file format issue. In his analysis, he posted a trend from IceRocket's Blogs+RSS search system:
So Audible largely won in the eyes of the media - the sole basis for how we used to define PR. Of course, we no longer live and die by traditional media alone. In the blogosphere it was an entirely different story, as this IceRocket trend graph shows.
I can't quite figure out what Steve means here: the trend shows what? That Audible didn't win in the eyes of the blogosphere? How does this graph show that? Another point of interest is the difference between the IceRocket trend and the BlogPulse trend (note that BlogPulse only shows hits for Blogs, not arbitrary RSS, so there are going to be some differences.)
I see two major differences here. IceRocket shows two large spikes - one in late August, the other in mid October. BlogPulse shows a single spike in early September. The other is the two smaller spikes in the BlogPulse trend (note that IceRocket has a couple of zero data points around the same time). BlogPulse allows you to drill down on specific dates. IceRocket doesn't have this, and as their custom date range query from the advanced search page is broken (it doesn't appear to work in either FireFox or IE), I can't yet determine what the spike in the IceRocket trend actually is.
The large spike found in BlogPulse is accounted for by quotes of a post by Brian Williams. The other two spikes appear to be associated with the Audible Inc. story - as this trend graph shows:
Here is the same trend on IceRocket:
I get a big kick out of trend graphs. However, it takes some care to work with them in the blogosphere. For example, every mention of the word 'audible' is not a mention of Audible Inc. - in fact, it probably the reverse. In addition, depending on what you trend over (blogs in the case of BlogPulse, RSS in the case of IceRocket) you see quite different results. If you are going to make any detailed use of trend graphs, you need the ability to inspect interesting features (either by drill down on the graph or by date specific queries).