We use data from millions of Substack posts and thousands of publications to determine what predicts success – from post frequency and pricing to word counts and category choice.
it would be interesting to use AI perhaps with some kind of validator to judge each writer's average complexity or writing IQ. For example, validate the classifier by showing as a strong correlation with an aggregate human judged complexity of a random subset of articles. This could replicate some old data I have where I asked my audience to rate the average content complexity of several different Substack authors in the right wing politics/intellectual sphere and found that there is a negative strong correlation between sophistication and popularity.
Yeah I recently analyzed 4000 HBD papers/books using the same method. The API from Google, which is quite cheap, only cost me a two dollars for this task. So I might at some later stage.
it would be interesting to use AI perhaps with some kind of validator to judge each writer's average complexity or writing IQ. For example, validate the classifier by showing as a strong correlation with an aggregate human judged complexity of a random subset of articles. This could replicate some old data I have where I asked my audience to rate the average content complexity of several different Substack authors in the right wing politics/intellectual sphere and found that there is a negative strong correlation between sophistication and popularity.
Yeah I recently analyzed 4000 HBD papers/books using the same method. The API from Google, which is quite cheap, only cost me a two dollars for this task. So I might at some later stage.
> Higher average subscription prices strongly correlate with higher estimated revenue.
What does this mean? I haven't read the rest of the post yet.