I wish to offer my sincere thanks for your assistance and willingness for the help and ideas in putting together a presentation and appear on the WUWT-TV event. Much of this came from reader’s ideas and insight.
We had a few technical glitches, we had a couple of embarrassing moments, and we had some great fun as well. The only criticisms that seemed to be pervasive was that it “wasn’t as well presented as Al Gore’s”.
Nothing could be truer, and nothing could be more illustrative of the disparity between the well funded “haves” and “have nots”. The next time somebody points to the meme “you skeptics are funded by big oil/big coal/ big something” all you need to do is point to this first effort, and that should shut them up because the entire WUWT effort was begged, borrowed, and donated from people “just like you” to borrow that PBS label.
In the process, I learned what to do and what not to do, and how to make the next effort better when we have to work on a limited budget. I think we won on the science content though.
Hilariously, we see still things like this coming from Gore during the event that tout that “big oil and “big coal” connection they imagine: http://realitydrop.org/about.
The video is priceless:
So, lessons learned, but we pulled it off, and I owe all of you a debt of gratitude. I’ll work to get YouTube recordings up next week. For now I need to rest a bit. Posting will be light this weekend.
Again, my sincerest thanks to all who contributed, participated, and watched. A special thanks to WUWT reader John Whitman who made two 300 mile round trip drives, battled a software learning curve, and spent over a week of his time working to bring us the “did you know” and Josh intermission slides. Thanks to Josh too.
Anthony Watts, and Kenji
P.S. suggestions are welcome for how to use/improve this new medium.
PPS. It seems much of Mr. Gore’s traffic may have been bot driven, see this analysis left in comments:
Submitted on 2012/11/16 at 2:54 pm
For fun, I was considering the proposition that each of the viewers of WUWT-TV and Gore-TV might belong to 1 of 2 populations:
X = population with a mean view time of 1 hr. (Watchers)
Y = population with a mean view time of T minutes. (Bots + thrashers)
Let T = average view time for the Y population.
Let TV = Total Views in 24 hours.
Let CV = Current Views average over 24 hr.
CV = X + Y
TV = 24* (X + Y*60/T)
X = CV*(60/(60-T)) – TV*(T/(24*(60-T)))
Y = CV – X
TV(WUWT) = 16,690 (what I remembered seeing. I could be wrong.)
CV(WUWT) = 550 is my guess at an average in a range of 420-670 from personal observation. Until we have something better.
TV(Gore) = 15.7 million (from mfo 02:28 prev. thread) . I cannot confirm that, but Reg. Blank above reports about million at 2.25 hours, about 10% into it.
CV(Gore) = 9000 @ TV=300K, 1.5 hr;
= 11200 @ TV=500K, 1.9 hr.
= 12100 @ TV “close to a million” at 2.25 hr. from Reg. Blank above.
Shortly after this the CV counter was taken down. So we will have to guess this by exploring a range of possible values. An important constraint here is that the three observation points give a mean view time of only 3 minutes (approx.).
Frac_TV_X = Fraction of TV that can come from X population (1 hr mean) views.
Frac_TV_X = X*24/TV
First, WUWT-TV: (TV=16690, CV=550)
If T=0.16, X=550, Y=0.4, Frac_TV_X = 0.790
If T=1, X=548, Y=2, Frac_TV_X= 0.787
If T=10, X=521, Y=29, Frac_TV_X = 0.749
So 74-79% of the TV (total views) are coming from the population views with a mean 1 hr.
Now Gore-TV: (TV = 15.7 million)
If CV = 36000 (3 times highest known value)
If T=0.16; X=34347; Y=1653; Frac_TV_X=0.053
If T=1; X=25523; Y=10477; Frac_TV_X=0.039
If T=2; X=14684; Y=21316; Frac_TV_X=0.022
If T=3; X=3465; Y=32535; Frac_TV_X=0.005
T>4 is not possible.
If CV=24000, T=0.16; X=22315; Y=1685; Frac_TV_X=0.034
If CV=50000, T=0.16; X=48385; Y=1615; Frac_TV_X=0.074
If CV=100000, T=0.16; X=98518; Y=1482; Frac_TV_X=0.151
Note: T=0.16 represents a viewer that is opening the stream and shutting it down in a 10 second loop. With T=0.16, X = watchers, Y = ‘bots.’
Conclusion: X is tightly coupled with the estimate for CV. But the fraction of total views from 1-hr Watchers is illuminating. The Frac_TV_X (= 1hr people views / total views) is highest for high CV and low T. For CV = 36000 (3 time higher than any reported in the first two hours) only 5% of the total views were from “watchers”, 95% from bots. We have to use CV=100,000 (8 times higher than max observed), to reach a point where even 15% of total views could be from a population with a 1 hr mean view. At least 85% of total views were bots cycling every 10 seconds.