Comment by yoan9224
2 days ago
This is a clever aggregation project, but I think the methodology might miss some important signal-to-noise distinctions. A book mentioned once in passing ("oh yeah, like in [book]") carries very different weight than a book recommended explicitly ("you should read [book] if you want to understand X"). Are you parsing comment sentiment or just doing keyword extraction?
The real value would be in clustering books by topic and showing which ones appear together in discussions. If someone mentions "Designing Data-Intensive Applications" and "Database Internals" in the same comment, that's a stronger signal than two isolated mentions. You could build a recommendation engine from that co-occurrence data.
Also curious about the temporal aspect - tracking which books surge during certain news cycles. For example, did "Chip War" mentions spike when the AI compute restrictions hit? That contextual analysis would make this way more useful than a static ranked list. Would definitely use this if it had those features.
It's already pretty useful with the number of mentions available. Higher a number, the more that generally find a work of interest. Unless there are members who just love to spam the names of particular books. My main gripe is that this isn't a repo/gist, as a site this specialized is more likely to disappear into the wind at any time. Also the Amazon buy links; would prefer a link to Wikipedia, or even Goodreads.