Google revealed in a blog post that it has updated its machine learning systems to identify and remove more fraudulent reviews, Google my business listings, images, and videos.

Over 200 million photos, 7 million videos, and over 115 million reviews were taken down by automated systems and human reviewers. This is a 20% increase from the year before, 2021.

How Google Finds Spam Contributed by Users?

Google is using brand-new models for machine learning to find and get rid of fake and fraudulent content.

These machine-learning models look for strange patterns in user-generated content, like new ways of abusing the system that hadn’t been seen before.

Google shared:

“We’ve long used machine intelligence to help us spot patterns of potential abuse, and we continue to evolve our technology.

Last year, we launched a significant update to our machine learning models that helped us identify novel abuse trends many times faster than in previous years.

For example, our automated systems detected a sudden uptick in Business Profiles with websites that ended in .design or .top — something that would be difficult to spot manually across millions of profiles.

Our team of analysts quickly confirmed that these websites were fake — and we were able to remove them and disable the associated accounts quickly.”

Before a new piece of content is added to Google Maps, its systems check it to make sure it isn’t fake or fraudulent.

They also use a machine learning model to check already published content for fake information that may have gotten past the first round of reviews.

These new systems catch more spam and stop it faster than in 2021.

Google explained:

“In some places, scammers started overlaying inaccurate phone numbers on top of contributed photos, hoping to trick unsuspecting victims into calling the fraudster instead of the actual business.

To combat this issue, we deployed a new machine learning model that could recognize numbers overlaid on contributed images by analyzing specific visual details and the layouts of photos.

With this model, we successfully detected and blocked the vast majority of these fraudulent and policy-violating images before they were published.”

Spam Blocking Statistics

Google’s announcement shared that in 2022:

  • Google blocked or removed over 115 million reviews, saying that the majority were blocked before being published.
  • The new spam fighting algorithms removed over 200 million photos and more than 7 million videos that violated Google’s content policies.
  • Blocked 20 million attempts to create fake business profiles.
  • Added heightened protection for over 185,000 businesses that were experiencing suspicious activities.
In January 2023, Google sent a comment to the FTC (you can read the PDF here). In it, Google said that, in addition to reading the content, it uses signals to find fake accounts.

Google also said that it is now scanning images to find content that is added to them to try to get people to call a scammer instead of a business.

They look for bots, duplicate content, and word patterns that are similar to those found in known fake reviews. They also use something they call “intelligent text matching,” which helps them find content that is misleading.

Real, safe, and dependable

Google tries to stop fake activity on the Google Maps ecosystem by using both automated and human reviewers.

Getting rid of fraud on Google Maps is important for both the people who rely on the reviews of businesses and the businesses that are listed in the system.