Obviously, if we were actually going to work through this data we would want to know the rate of best-movie-ranking rather than the absolute numbers. Just as importantly, we’d want to know the frequency of best-movie-ranking relative to the number of movies watched from each decade, such that best-movie-rankings aren’t simply dependent on availability.
In my experience, of the older movies I have watched, a greater fraction were strongly memorable than of the newer movies I have watched. In part, I suspect this is because I watch older movies intentionally, knowing that they are reputed to be good, where I watch newer movies with a somewhat lower bar for putting in the effort (because they are available in theaters, are easier to talk about, etc.).
Assuming the best old movies don’t get filtered out and stay available, this data is accurate for our purpose.
IMDB top list is based on Bayes-filtered ratings, it says what proportion of people watching the movie loved it, not how many people watched it. It will be automatically biased towards intentional watching (therefore old movies), and the bias is in my opinion fairly strong. Still, in spite of this new movies win.
To be clear, I agree that the list should be biased towards old movies in the manner you describe.
The total number of films created has been rising for a while, however (under the “Theatrical Statistics” report here, for instance). It’s not entirely unreasonable to believe that over 3x as many films were made in the 2000s as in the 1930s, though; compare Wikipedia’s lists of 1930s films and 2000s films. The latter is dramatically longer.
Like I said, we would want to know the fraction of films making the Top 250 list, not the absolute numbers.
It would also be interesting to apply the methods of _Human Accomplishment_, collating critical lists & histories other than IMDB, such as the rather grandiose “The Best 1,000 Movies Ever Made ” from the New York Times. I would very much expect a recency effect.
Obviously, if we were actually going to work through this data we would want to know the rate of best-movie-ranking rather than the absolute numbers. Just as importantly, we’d want to know the frequency of best-movie-ranking relative to the number of movies watched from each decade, such that best-movie-rankings aren’t simply dependent on availability.
In my experience, of the older movies I have watched, a greater fraction were strongly memorable than of the newer movies I have watched. In part, I suspect this is because I watch older movies intentionally, knowing that they are reputed to be good, where I watch newer movies with a somewhat lower bar for putting in the effort (because they are available in theaters, are easier to talk about, etc.).
Assuming the best old movies don’t get filtered out and stay available, this data is accurate for our purpose.
IMDB top list is based on Bayes-filtered ratings, it says what proportion of people watching the movie loved it, not how many people watched it. It will be automatically biased towards intentional watching (therefore old movies), and the bias is in my opinion fairly strong. Still, in spite of this new movies win.
To be clear, I agree that the list should be biased towards old movies in the manner you describe.
The total number of films created has been rising for a while, however (under the “Theatrical Statistics” report here, for instance). It’s not entirely unreasonable to believe that over 3x as many films were made in the 2000s as in the 1930s, though; compare Wikipedia’s lists of 1930s films and 2000s films. The latter is dramatically longer.
Like I said, we would want to know the fraction of films making the Top 250 list, not the absolute numbers.
It would also be interesting to apply the methods of _Human Accomplishment_, collating critical lists & histories other than IMDB, such as the rather grandiose “The Best 1,000 Movies Ever Made ” from the New York Times. I would very much expect a recency effect.