• TropicalDingdong@lemmy.world
    link
    fedilink
    arrow-up
    1
    arrow-down
    2
    ·
    22 days ago

    So it seems like your argument is that podcasts on captured platforms use downloads, not views as rankings, we have to use that instead. But also, we don’t have access to that data. Because of this, it seems implied in your second paragraph (and you’ve mentioned it before) that we should use $$ as a proxy for viewership (since we can’t measure viewership directly) assuming our goal here is still to get these podcasts off of a discrete scale and into a more continuous scale.

    Which is like totally fair, except that only very public shows/podcasts etc are going to publish those numbers. It’s a totally valid way to do it, but it comes to the same issue I identified previously, we only have limited access and we can’t put a number down for each data point. I know we can pretty easily map views to $$ on YouTube. And if we assume a $ is a $ and is roughly equivalent to a similar number of views, we can get to an apples to apples comparison.

    I don’t agree with this:

    And while I know official music videos get a lot of watches on YouTube, I don’t think counting those watches are a good way to rank or analyze how people “listen” to music overall.

    I don’t agree. I think yt views are the least plagiarisable metric we have access to. And it’s the only one we have access to that’s a uniform proxy across all the discussants. Every single podcast or show also puts the same stuff in YT.

    I would rank the reliability of continuous metrics for this conversation at YT views or comments first, then if accessable, downloads, then dollar amounts (published or derived from yt views).

    I think we could pick a set of what we anecdotally consider ‘top’, ‘mid’, and ‘basic’, teir shows or podcasts (there’s no real difference in my mind; I’m watching the same seder show rn: but I’m not I’m listening to it.). If we can get maybe 3-6 for each tier, and we can get them for “Call Her Daddy”, we can evaluate the podcast via all three metrics. We could then weight the three metrics individually and average the two.