2 ms·

I believe the way the algorithm works is it looks for how credible a given complaint is based on many factors. If I had to guess, they'll look at the age of the

by jmtame 15y ago

I believe the way the algorithm works is it looks for how credible a given complaint is based on many factors. If I had to guess, they'll look at the age of the user account, how active it is, how many other reviews are written by the user. A user who just created an account and wrote a negative review against Yelp is probably going to be filtered out because that user isn't a regular reviewer. A more compelling argument would take all the users that were filtered and analyze their history. That's where the interesting data is, so show me that and convince me that Yelp's algorithm is bad. Don't just say "Look at how difficult reCaptcha is, Yelp must be up to something here." When has any implementation of captcha ever been easy to use? That original article says that the users banded together to write positive reviews over a short period of time. We don't know whether the business owner incentivized them or if they just did that altruistically. The facts are simply not known, the best we can do is make assumptions there (which makes for a pretty weak argument to begin with). Banding together and writing reviews with the sole purpose of boosting a business' online reputation is what really happened here, and Yelp specifically designed their algorithm to deal with those use cases. The actual pattern businesses follow for building a reputation is very incremental: positive reviews spread over time, not a short burst by people who aren't actively using the site to review other businesses. To make a compelling case, rather than what appears as a rant in its current form, you need more data. You need to show that the users are active on Yelp and they aren't afraid to write both positive and negative reviews to reflect their true experiences. Banding together in groups to write positive reviews is basically the same thing as submitting a story to HN and getting all your friends to upvote it.

Goladus 15y ago
You need to show that the users are active on Yelp and they aren't afraid to write both positive and negative reviews to reflect their true experiences. That shouldn't be necessary. I've written like, five reviews ever and they're all honest, I have a few friends that have written reviews and they seem to average one review every few years or so. Meanwhile I've seen reviews from elites that are well-written but absolutely pointless for me. Sometimes it's as if they're writing more to impress other reviewers than to actually give me any useful information. Banding together and writing reviews with the sole purpose of boosting a business' online reputation is what really happened here, and Yelp specifically designed their algorithm to deal with those use cases. Why filter the reviews entirely instead of just sorting them down or something? Especially if they seem more or less legit except there's a small bunch all at once? Banding together to boost an online business's reputation really should not be cause for filtration. Fake accounts, bots, lies, and attempts to bury negative information are problems. A bunch of loyal customers who hear about yelp from the owner and want to write a review is quite simply not a problem and yelp shouldn't be doing anything about it. And why discriminate against businesses that don't sell advertising?
- jmtame 15y ago
  Banding together to boost an online business's reputation really should not be cause for filtration. Fake accounts, bots, lies, and attempts to bury negative information are problems. How do you algorithmically distinguish between the two? To Yelp, someone who signs up for an account and writes one positive review is the exact same thing as a script written to create bots that go off and write one positive review. They're both identical. And the bots' behavior can change to write more reviews to prevent looking like a bot. Business reputations take time, so when Yelp's algorithm sees "this business has been around since 1975, and 100% of its positive reviews just came in over the past 10 months, where 100% of its reviews were previously negative before that", that should be a red flag. I can't find the age of Frank's dog training business on Yelp; I searched and I didn't see it listed. So I can't say for certain whether the age of his business on Yelp had to do with the algorithm flagging the reviews. And why discriminate against businesses that don't sell advertising? Yelp is letting you bump up your flagged reviews if you pay an advertising fee. If Yelp's algorithms don't trigger any red flags, positive reviews should show up unfiltered on your page whether you pay for advertising or not.
  - Goladus 15y ago
    How do you algorithmically distinguish between the two? Maybe it can't. It doesn't matter you use a linear or binary search if the program isn't fed valid data. I'm suggesting they are using an algorithm to solve a problem that it shouldn't be used to solve. And the bots' behavior can change to write more reviews to prevent looking like a bot. Business reputations take time, so when Yelp's algorithm sees "this business has been around since 1975, and 100% of its positive reviews just came in over the past 10 months, where 100% of its reviews were previously negative before that", that should be a red flag. Interesting that you use the term "red flag" since that usually means a "warning" or "needs attention." There's a world of difference between using an algorithm to raise red flags, and using an algorithm to automatically prune content. In fact, a three-decades old small business with a lone, 1-star review should raise a red flag about the 1-star review.
derwiki 15y ago
Business owners soliciting reviews was the reason that (at least) one lawsuit against Yelp was dismissed, and I'd imagine flashmobs of high ratings are particularly easy to detect algorithmically.

by jmtame 15y ago

Goladus 15y ago

You need to show that the users are active on Yelp and they aren't afraid to write both positive and negative reviews to reflect their true experiences. That shouldn't be necessary. I've written like, five reviews ever and they're all honest, I have a few friends that have written reviews and they seem to average one review every few years or so. Meanwhile I've seen reviews from elites that are well-written but absolutely pointless for me. Sometimes it's as if they're writing more to impress other reviewers than to actually give me any useful information. Banding together and writing reviews with the sole purpose of boosting a business' online reputation is what really happened here, and Yelp specifically designed their algorithm to deal with those use cases. Why filter the reviews entirely instead of just sorting them down or something? Especially if they seem more or less legit except there's a small bunch all at once? Banding together to boost an online business's reputation really should not be cause for filtration. Fake accounts, bots, lies, and attempts to bury negative information are problems. A bunch of loyal customers who hear about yelp from the owner and want to write a review is quite simply not a problem and yelp shouldn't be doing anything about it. And why discriminate against businesses that don't sell advertising?

jmtame 15y ago
Banding together to boost an online business's reputation really should not be cause for filtration. Fake accounts, bots, lies, and attempts to bury negative information are problems. How do you algorithmically distinguish between the two? To Yelp, someone who signs up for an account and writes one positive review is the exact same thing as a script written to create bots that go off and write one positive review. They're both identical. And the bots' behavior can change to write more reviews to prevent looking like a bot. Business reputations take time, so when Yelp's algorithm sees "this business has been around since 1975, and 100% of its positive reviews just came in over the past 10 months, where 100% of its reviews were previously negative before that", that should be a red flag. I can't find the age of Frank's dog training business on Yelp; I searched and I didn't see it listed. So I can't say for certain whether the age of his business on Yelp had to do with the algorithm flagging the reviews. And why discriminate against businesses that don't sell advertising? Yelp is letting you bump up your flagged reviews if you pay an advertising fee. If Yelp's algorithms don't trigger any red flags, positive reviews should show up unfiltered on your page whether you pay for advertising or not.
- Goladus 15y ago
  How do you algorithmically distinguish between the two? Maybe it can't. It doesn't matter you use a linear or binary search if the program isn't fed valid data. I'm suggesting they are using an algorithm to solve a problem that it shouldn't be used to solve. And the bots' behavior can change to write more reviews to prevent looking like a bot. Business reputations take time, so when Yelp's algorithm sees "this business has been around since 1975, and 100% of its positive reviews just came in over the past 10 months, where 100% of its reviews were previously negative before that", that should be a red flag. Interesting that you use the term "red flag" since that usually means a "warning" or "needs attention." There's a world of difference between using an algorithm to raise red flags, and using an algorithm to automatically prune content. In fact, a three-decades old small business with a lone, 1-star review should raise a red flag about the 1-star review.

derwiki 15y ago

Business owners soliciting reviews was the reason that (at least) one lawsuit against Yelp was dismissed, and I'd imagine flashmobs of high ratings are particularly easy to detect algorithmically.