Good catch, not intentional, that's a bug. The sampler picks indices evenly spaced across the account's whole comment history, but it walks newest-to-oldest and bails out as soon as it fills a 90k-char budget. For any reasonably active account, that budget gets used up before the walk reaches old comments, so the model ends up looking almost entirely at recent activity even though the code intends an even sample across time.
Comments
That's kinda neat, actually.
The summary appears to have a pronounced recency bias. Is that intentional?
Good catch, not intentional, that's a bug. The sampler picks indices evenly spaced across the account's whole comment history, but it walks newest-to-oldest and bails out as soon as it fills a 90k-char budget. For any reasonably active account, that budget gets used up before the walk reaches old comments, so the model ends up looking almost entirely at recent activity even though the code intends an even sample across time.