Chatmeter Blog

How Does Google Places Select SERP Reviews?

Posted by collin on Jan 20, 2011 7:14:45 PM

It’s the question everyone seems to be asking: how does Google choose the reviews that are displayed prominently on Google Places and Google Maps? For example, when searching for “San Diego Restaurants” on Google Places, each Place on page 1 is displayed with a single review as a summary of the business:


So how does Google select that review?  Well, we don’t know exactly, but we have some ideas about the factors that Google is looking to. According to a patent filed on November 2, 2010, Google’s latest review system is looking at the reputations of the reviewers as a means of sorting reviews and selecting the ones that will be displayed prominently.  In addition, Google has come up with a way of rating the individual reviews, so the rated value of each review is also a factor. Bill Slawski, over at, summarizes the patent with these interesting observations:

  • “Some Reviewers or Raters can have negative reputations, and their reviews and ratings may not count in the final scores for the things, organizations, people, and other raters or reviewers being scored.
  • When reviewers provide only negative reviews or ratings, their contributions may not count.
  • In addition to creating a reputation score for reviewers and raters, this system includes reputation scores for reviews themselves.
  • This system attempts to anticipate the possibility of people attempting to manipulate it. For instance, if someone’s reviews are highly rated, it’s possible that their reputation score would increase. But, the reputation score for that reviewer depends upon the reputation scores for the people rating his or her review. If their reputation scores aren’t very good, then their positive ratings won’t have much of an impact. Likewise, someone receiving poor ratings for their reviews wouldn’t have their reputation score being affected tremendously if those raters had low reputations.” (

All of this means that Google definitely looks at two things when selecting the review that is displayed prominently on Google Places: (1) the reputation score of the reviewer, & (2) the reputation score of the review itself. One of our interns here at chatmeter has a theory that Google also looks to the average review 5 star rating and selects the review displayed a prominent review that correlates to the average review score. In other words, if your business has a lot of bad reviews and a 2 out of 5 star rating, the review displayed on a Google Places search page would be negative. On the other hand, if you mostly have positive reviews and a 5 out of 5 star rating, your review will be positive.  This is so basic that it seems like a no brainer, but maybe there is a more mathematical approach of coming to the same conclusion. By a more mathematical approach, I mean something Google calls “Aspect-based sentiment summarization.”  You can read Google’s White Paper on the subject for more information. To summarize what the Google paper explains much more scientifically, Google uses complex equations that attempt to summarize the sentiment of all listed reviews. Google does this by assigning positive, negative, and neutral values to specific words in specific markets.  For example, the word “small” in the hand-held electronics market would be assigned a positive value because people want thin laptops and sleek phones, but in the restaurant market “small” would be assigned a negative value for obvious reasons. This means that Google is utilizing a very complex system that assigns positive or negative values to specific words based on market research.  Presumably, Google then uses this data to split the reviews and select a key sentence or phrase that captures the overall sentiment of the average reviews and displays that sentence or phrase prominently on Google Places. So in summary, there are four possible factors that Google may be looking to when it selects the reviews displayed on its Google Places and Google Maps search results page: (1) the reputation of the reviewer, (2) the reputation of the review, (3) the reputation/rating of the business, (4) Google’s sentiment summarization formula that prioritizes specific words and/or positive or negative messages depending on the average of all reviews listed. Well, that’s all for now folks, let us know what you think about all this.

Topics: Google, Local Search, Local SEO, Local Search Rankings, Local SEO, Reviews

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