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Google Reveals Its Methods for Detecting False Reviews of Local Businesses

Google has released a paper detailing how it identifies and removes phony profiles and reviews for businesses. Google has enhanced its machine learning systems to detect and eliminate additional fraudulent content, including phony reviews, bogus business listings, and fraudulent donated photographs and videos, according to a blog post published by the company.

Twenty percent more reviews were deleted or prohibited in 2022 than in 2021 thanks to automatic technologies and human review teams removing almost 200 million photographs, 7 million videos, and over 115 million reviews.

The Methods Google Uses to Detect Spam That Users Post

Google is employing cutting-edge machine learning models to identify and delete malicious or misleading information.

In order to identify previously unseen kinds of abuse, these machine learning algorithms scan user-generated information for any anomalies.

“We’ve used machine intelligence for a long time to help us identify patterns of potential abuse, and we’re always working to improve our technology,” Google said.

We were able to spot brand-new abuse tendencies at a far quicker clip after releasing a major update to our machine learning models last year.

For instance, our software saw a spike in the number of Business Profiles with domains ending, something that would be really difficult to notice by eye across millions of profiles.

Our research team soon determined that these sites were fraudulent, and we promptly took down the domains and disabled the accounts linked with them.

To prevent malicious or fraudulent material from being added to Google Maps, the company’s algorithms perform quality checks on all new submissions.

They use a machine learning algorithm to look through published information as well, in case any fakery snuck past the first checks.

Spam is stopped more quicker and more efficiently by these modern methods than it was in 2021.

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