How honest are you when mistakes are made in your favor? I bet it depends on your relationship to the mistake maker. If it’s your friend you’ll hapilly point out the confusion (You gave me a $20, not a $5). But if it’s a faceless corporation/government/evil empire, you might keep quiet and pretend you didn’t notice (extra doughnut for me!).
Well what to do about blog rankings? I know how many problems there are for ranking anything (e.g. The academy awards, sports MVPs) but since the blog ranking systems are automated, based on volume, there’s no end to disagrements about which ones are more accurate. Even though equating various kinds of link volume with popularity has various problems.
I know this because I showed up on Feedsters top 500 list at a not quite under the wire 463. Which is odd given that this blog, so far, is low volume, low profile, and mostly about a recently published, and relatively unknown, book. It’s not exactly a mistake: they had some algorithm which produced a list. But many notable high profile blogs didn’t make it, and some odd underlings (this blog) made the cut. I’m holding an undeserved doughnut.
But the most curious thing for me is how despite the belief that blogs exemplify the diversity and freedom of expression that the net empowers, we all still (myself included) are drawn back to single file all inclusive stacked ranked lists. We like to give ourselves a number (Insert favorite flashback to the Prisoner here). We’re compelled, even when it makes us unhappy, to seek out definitive measurements of things.
Instead, it’d be nice to poke at the list, categorize it in different ways, and make it relevant to my interests. I’d like to filter it on sources of links- who are kottke.org‘s or boingboing top ten link targets? – but none of the blog list makers have made their popularity lists flexible, yet.
In specific: I’d rather know who’s popular with the 3 or 4 people I find most interesting, rather than what’s popular with 100,000 people I don’t care about, have no shared interests with or who possibly have the collective IQ of a sack of marbles (present company excluded). Big formula based lists, from big piles of data, run the risk of averaging and rounding out much of what’s interesting.
Coming soon: the difference between popularity and quality.