41–50 of 124 posts
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That's awful. Has no one automated the process of checking for bogus reviews and reporting them?
How do you tell a bogus review from a real one, except by having it actually read by a human? This would be pretty expensive.
Earlier quoted context omitted.
That's awful. Has no one automated the process of checking for bogus reviews and reporting them?
How do you tell a bogus review from a real one, except by having it actually read by a human? This would be pretty expensive.
Much like search engines combat black hat SEO, amazon and reviews systems can do the same. It would not be to hard too for amazon. Use reviews that are a 'Verified Purchase' and highly 'helpful' reviews as a training/test set. Then machine learn a weighting to every review based on the (product, reviewer, other reviews, etc features...) The outcome could actually hinder tactics like this for products that game the sy…
Earlier quoted context omitted.
That's awful. Has no one automated the process of checking for bogus reviews and reporting them?
How do you tell a bogus review from a real one, except by having it actually read by a human? This would be pretty expensive.
In light of that recent article about computer-generated prose being in many cases indistinguishable from human-written, I'd say those fake reviews are likely written by a computer. Notice that they're mostly of the form "I didn't think I'd be interested in [TOPIC] but [TITLE] was really interesting and really helped me learn about [TOPIC]."
That's an interesting thought. I'm pretty sure I could write up a nice grammar to chunk out "interesting" reviews of books. Instead of whining about my book getting buried by fake reviews, maybe I should chuck it and cache in on said reviews!
We can see this happening in the case of SEO with many white hat sites employing black/gray hat techniques simply to maintain their current positions in Google.
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There should be very obvious ways to identify "review bots" - especially given that reviews are tied to an amazon accounts purchase and browsing history. That they don't have an efficient algorithm for this sounds more like they don't really care and never bothered with it.
I'd say it's more likely that this is a complex problem, and will take a bit of time and computing power to work through... Amazon has hundreds of thousands of products with tens of millions of reviews... correlating that with log history for each review will take a lot of time... not just to run, but to write any automated process, and work through resolving it. It seems to me that Amazon seems to be pretty responsi…
It is a complex problem - but amazon has a serious advantage over other sites that have to deal with such issues (i.e. Twitter) - in that they have significantly more information on each user. I don't think Amazon is short on computing power either.
Taking into account order and browsing history, product review trends, linguistic similarities in review posts etc. They should be able to get very low error rates in identification.
Further unlike something like twitter feeds, it's quite possibly to silently de-prioritize abusive reviewers and associated products. Really, I'm quite surprised at how bad of a job they are doing - most of these cases are so blatant and obvious they should not require an author and a live representative to resolve.
Earlier quoted context omitted.
That's awful. Has no one automated the process of checking for bogus reviews and reporting them?
How do you tell a bogus review from a real one, except by having it actually read by a human? This would be pretty expensive.
What's bad (really bad) here, is that not only are the books that are being ranked highly absolute crap, but they are crap in different categories. I.E. A "book" on swift, that was apparently "written", in a few hours, shoved onto Amazon, falsely ranked up - now ranks ahead of a 700 page opus on Perl, in the Perl category.
That's a total fail on Amazon's part, and really, really disappointing.
In light of that recent article about computer-generated prose being in many cases indistinguishable from human-written, I'd say those fake reviews are likely written by a computer. Notice that they're mostly of the form "I didn't think I'd be interested in [TOPIC] but [TITLE] was really interesting and really helped me learn about [TOPIC]."
That's an interesting thought. I'm pretty sure I could write up a nice grammar to chunk out "interesting" reviews of books. Instead of whining about my book getting buried by fake reviews, maybe I should chuck it and cache in on said reviews!
How about writing high-quality responses to the bad reviews? I have seen this done by some authors and it usually stops the meaningless reviews, since each additional spam review only creates a new opportunity for the author to present their marketing perspective via comment. If this were a novel, economically hostile and unsubstantiated feedback would be considered economic warfare.