3 ms·

The channels follow a power law. I got the number of views from here (http://socialblade.com/youtube/top/5000 http://socialblade.com/youtube/top/5000) and plot

The channels follow a power law. I got the number of views from here (http://socialblade.com/youtube/top/5000 http://socialblade.com/youtube/top/5000) and plotted them: http://i.imgur.com/X6nEL.png http://i.imgur.com/X6nEL.png If the $23k average for the top 1k is correct, then only the top 250 or so actually make $23k a month or more. At that line are some pretty big channels, like Husky Starcraft and big bands like Kesha and Muse. In which case, this doesn't seem like a lot of money.

ChuckMcM 14y ago
That is an awesome plot. That combined with a combined with a tenancy plot to determine what sort of churn there is in the top 500 and its mix would really illustrate what sort of 'opportunity' YouTube is.
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- saurik 14y ago
  The way people normally plot these kinds of distributions is on a log/log graph (to be clear: where both axes are log'd, not where only one of the axes is doubly-log'd).
  - rorrr 14y ago
    That's not true, only if the distribution in both directions is exponential, which is not the case here. The horizontal scale is just the rank, which is linear.
    - saurik 14y ago
      Interesting; FWIW, I am going based on the comment "the channels follow a power law" from the grandparent post. I was under the (possibly mistaken) impression that these are normally plotted using log-log; would you be willing to explain what I am getting wrong? (I am totally happy to believe I'm missing something btw, and I certainly did not anticipate the person I responded to deleting their post...). (edit: Further, looking at the graphs, it certainly seems like they would do well on a log-log chart; also, I would have expected the behavior that was described in the deleted post from a distribution of this sort: specifically, where further introductions of logarithms to the same axis did not affect the result, as they were asymptotically identical.)
      - rorrr 14y ago
        The parent is obviously wrong about power law (like e^x). It's not even e^(e^x), it's something that grows more rapidly, like x^x, or x factorial. I'm too lazy to figure it out.
    - muyuu 14y ago
      Rank can be considered linear or logarithmic. It can be argued that the difference between being 1st or 10th is orders of magnitude bigger than the difference between being 100th and 110th. In fact I think a log scale for rank usually makes the most sense, especially when starting from 1st.
    - hyperbovine 14y ago
      The parent is correct, the claimed relationship being y ~ rank^a for some a<0. You would want to see a linear relationship on the log log plot. Another choice would be to examine the complmentary CDF P(X > x) and look for power law tails.
      - rorrr 14y ago
        > The parent is correct, the claimed relationship being y ~ rank^a for some a<0 You clearly don't know the difference between exponential and polynomial relationship. rank^a is polynomial. a^rank is exponential. The data is neither (unless you can demonstrate it with the actual formula).
        hyperbovine 14y ago
        I don't really have time to do this because I'm supposed to be working on a paper about, wait for it, power laws, but I went ahead and re-plotted the data using log-log axes. Sure enough, it's linear as would be expected for power law type behavior: http://imgur.com/qdWxr http://imgur.com/qdWxr I suggest you start with http://www.hpl.hp.com/research/idl/papers/ranking/ranking.html http://www.hpl.hp.com/research/idl/papers/ranking/ranking.ht....
        rorrr 14y ago
        Well of course, pretty much any data looks linear on a log-log chart. The real question here is what the formula is between the rank and the number of views. You absolutely cannot derive it from the log-log chart. My point from the beginning is that it's not a power law (y=c*a^bx, where y = views, x = rank and the rest is constants).
        hyperbovine 14y ago
        > Well of course, pretty much any data looks linear on a log-log chart. Hah! If you seriously believe that, I've got some stock options I'd like to sell you...
rorrr 14y ago
I charted the LOG(video views) here: http://i.imgur.com/WubeX.png http://i.imgur.com/WubeX.png What's really interesting is that LOG(LOG(video views)) looks pretty much the same: http://i.imgur.com/NnSrA.png http://i.imgur.com/NnSrA.png So I'm not sure what law the distribution follows, but the top players get a TON more money than the rest. The top 211 players make more than the rest 4789. EDIT: It also means that the top player universalmusicgroup makes $485,707/month, and the 1000th player playboy makes only $7,880/month (assuming payouts are proportional to the views, which isn't perfectly correct) Here's the table: universalmusicgroup $485,707 machinima $261,804 JustinBieberVEVO $206,638 RihannaVEVO $198,898 expertvillage $182,052 LadyGagaVEVO $160,885 AtlanticVideos $147,373 EminemVEVO $145,593 RayWilliamJohnson $141,569 IGNentertainment $139,634 failblog $134,727 UltraRecords $134,724 muyap $126,330 smosh $124,425 shakiraVEVO $122,633 hollywoodrecords $121,395 FueledByRamen $113,681 beyonceVEVO $109,576 barelypolitical $104,784 collegehumor $103,772
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majani 14y ago
Note that syndication is very popular with the top channels, so you have top creators like RWJ owning 3 of the top 1000 channels, VEVO owning more than 50, same with machinima.com, Demand Media and others which I might have missed. That skews the power law even further.

ChuckMcM 14y ago

That is an awesome plot. That combined with a combined with a tenancy plot to determine what sort of churn there is in the top 500 and its mix would really illustrate what sort of 'opportunity' YouTube is.

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saurik 14y ago
The way people normally plot these kinds of distributions is on a log/log graph (to be clear: where both axes are log'd, not where only one of the axes is doubly-log'd).
- rorrr 14y ago
  That's not true, only if the distribution in both directions is exponential, which is not the case here. The horizontal scale is just the rank, which is linear.
  - saurik 14y ago
    Interesting; FWIW, I am going based on the comment "the channels follow a power law" from the grandparent post. I was under the (possibly mistaken) impression that these are normally plotted using log-log; would you be willing to explain what I am getting wrong? (I am totally happy to believe I'm missing something btw, and I certainly did not anticipate the person I responded to deleting their post...). (edit: Further, looking at the graphs, it certainly seems like they would do well on a log-log chart; also, I would have expected the behavior that was described in the deleted post from a distribution of this sort: specifically, where further introductions of logarithms to the same axis did not affect the result, as they were asymptotically identical.)
    - rorrr 14y ago
      The parent is obviously wrong about power law (like e^x). It's not even e^(e^x), it's something that grows more rapidly, like x^x, or x factorial. I'm too lazy to figure it out.
  - muyuu 14y ago
    Rank can be considered linear or logarithmic. It can be argued that the difference between being 1st or 10th is orders of magnitude bigger than the difference between being 100th and 110th. In fact I think a log scale for rank usually makes the most sense, especially when starting from 1st.
  - hyperbovine 14y ago
    The parent is correct, the claimed relationship being y ~ rank^a for some a<0. You would want to see a linear relationship on the log log plot. Another choice would be to examine the complmentary CDF P(X > x) and look for power law tails.
    - rorrr 14y ago
      > The parent is correct, the claimed relationship being y ~ rank^a for some a<0 You clearly don't know the difference between exponential and polynomial relationship. rank^a is polynomial. a^rank is exponential. The data is neither (unless you can demonstrate it with the actual formula).
      - hyperbovine 14y ago
        I don't really have time to do this because I'm supposed to be working on a paper about, wait for it, power laws, but I went ahead and re-plotted the data using log-log axes. Sure enough, it's linear as would be expected for power law type behavior: http://imgur.com/qdWxr http://imgur.com/qdWxr I suggest you start with http://www.hpl.hp.com/research/idl/papers/ranking/ranking.html http://www.hpl.hp.com/research/idl/papers/ranking/ranking.ht....
        rorrr 14y ago
        Well of course, pretty much any data looks linear on a log-log chart. The real question here is what the formula is between the rank and the number of views. You absolutely cannot derive it from the log-log chart. My point from the beginning is that it's not a power law (y=c*a^bx, where y = views, x = rank and the rest is constants).
        hyperbovine 14y ago
        > Well of course, pretty much any data looks linear on a log-log chart. Hah! If you seriously believe that, I've got some stock options I'd like to sell you...

rorrr 14y ago

I charted the LOG(video views) here: http://i.imgur.com/WubeX.png http://i.imgur.com/WubeX.png What's really interesting is that LOG(LOG(video views)) looks pretty much the same: http://i.imgur.com/NnSrA.png http://i.imgur.com/NnSrA.png So I'm not sure what law the distribution follows, but the top players get a TON more money than the rest. The top 211 players make more than the rest 4789. EDIT: It also means that the top player universalmusicgroup makes $485,707/month, and the 1000th player playboy makes only $7,880/month (assuming payouts are proportional to the views, which isn't perfectly correct) Here's the table: universalmusicgroup $485,707 machinima $261,804 JustinBieberVEVO $206,638 RihannaVEVO $198,898 expertvillage $182,052 LadyGagaVEVO $160,885 AtlanticVideos $147,373 EminemVEVO $145,593 RayWilliamJohnson $141,569 IGNentertainment $139,634 failblog $134,727 UltraRecords $134,724 muyap $126,330 smosh $124,425 shakiraVEVO $122,633 hollywoodrecords $121,395 FueledByRamen $113,681 beyonceVEVO $109,576 barelypolitical $104,784 collegehumor $103,772

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majani 14y ago

Note that syndication is very popular with the top channels, so you have top creators like RWJ owning 3 of the top 1000 channels, VEVO owning more than 50, same with machinima.com, Demand Media and others which I might have missed. That skews the power law even further.