bpp000007•

i’m surprised the omer aziz episode isn’t there

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HyperSplineOP•

The Omar Aziz episode was in 16th place with 336 comments. That was an earlier episode, so maybe that's why there aren't as many comments.

Here are the top 20:

  1. Scott Adams

  2. Jordan B. Peterson

  3. Charles Murray

  4. Jordan B. Peterson

  5. David Benatar

  6. Gary Taubes

  7. Eric Weinstein & Ben Shapiro

  8. Douglas Murray

  9. Anne Applebaum

  10. Anne Applebaum & Juliette Kayyem

  11. Joseph Romm

  12. Mark Lilla

  13. Gavin de Becker

  14. James Kirchick

  15. Timothy Snyder

  16. Omer Aziz

  17. Nicholas Christakis

  18. David Frum

  19. Thomas Metzinger

  20. David Frum

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sjeffiesjeff•

Yeah these are pretty heavily skewed towards newer podcasts.

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LivingReceiver•

No Maryam Namazie is a surprise too

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LordOssus•

I don’t think it’s controversial, in the sense the sense most of us probably agree how painful it was to listen to that episode.

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hippydipster•

The data probably needs to be adjusted for number of members of the sub at the time

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HyperSplineOP•

I made a barplot of Sam's 10 most controversial podcast episodes. The metric I used to quantify "episode controversy" was the number of comments in the official episode thread on this sub. The three most controversial episodes were (perhaps unsurprisingly) Triggered (w/ Scott Adams), Meaning & Chaos (w/ Jordan Peterson), and Forbidden Knowledge (w/ Charles Murray).

I was unable to find the official thread for a few episodes (#1, #8, #12, #15, #20, #30, #31, #35, #55, #56, #85), so those episodes were not considered in this analysis. Additionally, the more recent episodes tended to have more comments due to the growth of this sub, so that might have skewed the results somewhat. The plot was made in R.

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R1ppedWarrior•

The data is interesting and you visualized it well! Why did you choose to use total comments as an indication of controversy? I would think the number of comments would directly relate to popularity not controversy.

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Strange_Vagrant•

And sub popularity, and time of week the pod and threads opened, and a lot of other factors.

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HyperSplineOP•

Thanks. That's a good point. Maybe "popularity" would have been a better word here than "controversy." It's just that the episodes with the most comments were not necessarily the best (IMO), and they seem to have been the most controversial. I actually thought for a long time about the best word to use, and settled on controversial.

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jeegte12•

it's also not popularity because we have more and more subs towards the later episodes.

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dsgstng•

If it's a popular but not controversial episode, people are more likely to just upvote one of the top comments if they even bother to go to this subreddit. If it's a controversial episode people will want to discuss and chime in themselves more.

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LondonCallingYou•

The plot was made in R.

Love ggplot

Additionally, the more recent episodes tended to have more comments due to the growth of this sub

Did you think about normalizing wrt number of subscribers or number of listens on the episode? While not perfect, it would account for this a bit

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HyperSplineOP•

I wanted to normalize by the number of subscribers to this sub, but I couldn't find that information. Normalizing by the number of episode listens is a good idea, and not one that I had thought of. I'll probably make another plot like this when Sam reaches 200 episodes, and I'll consider normalizing by number of episode listens then.

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LondonCallingYou•

Here's a site you can use to find number of subscribers at any given date

Number of listens may be a better number to normalize to, though. I'm sure you can play around with the data and make it make sense.

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HyperSplineOP•

Perfect. That will be useful.

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zen-trader•

I think downvotes (or downvote/upvote ratio) could also factor in as a metric. Good project. Will be interesting to see future iterations.

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Im_That_Guy21•

Interesting visualization! Did you adjust the numbers to take growth of the subreddit into account? Episodes that are posted to a subreddit with more subscribers would likely have more comments. What you could do is take the total number of comments and divide it by the total number of subscribers at the time the episode was posted, and express the histogram as a percentage of subscribers.

I'm not sure if the subreddit has been growing quickly enough (or at all?) for this to matter, but it may change some of the results.

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