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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 in

by 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.

by jmtame 15y ago

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.