Many comparable filters seem to kick into action if any of the following is present in the content of the review:
1. Use of extreme adjectives or profanity in the review
2. Over-use of keywords in the review
3. Inclusion of links in the review
Another criterion that also tends to trigger filtering is a sudden burst of reviews preceded by or followed by a long lull between them.
Some of the more sophisticated review filters, including (Google &) Yelp’s, take a look at user characteristics, too, including:
a) Total number of reviews a user has left on the site
b) Distribution of ratings across all of a user’s reviews
c) Distribution of business types among all of a user’s reviews
d) Frequency of reviews that a user has left on the site
e) IP address(es) of the user when leaving reviews
The bottom line is that reviews written by active users have an astronomically-higher likelihood of “sticking” on a local search engine than those written by first-time or infrequent reviewers. And even beyond their stickiness, many local search experts (including myself) speculate that reviews left by active users also influence rankings to a much greater extent than those left by first-time or infrequent reviewers.
