Google has released its new Google Maps and local spam fighting numbers for the 2023 year, citing a big lift in reviews and other local fraud that was blocked. Google credited a new machine learning algorithm and its spam-fighting team for the improvements. You can see the previous years at 2022, 2021, 2020 and 2019 for those data points.
Google said it blocked 45% more policy-violating reviews from this year compared to last year, 100% more policy-violating videos and the rest of the numbers don't really line up for me from previous years.
Google removed or blocked over 170 million fake reviews, 12 million fake Business Profiles, 14 million policy-violating videos, over 2 million attempts to make fake Business Profiles, and more. Google left out the photos number, and changed how they measure removal of the business profiles.
Google told me, "We're not sharing our number for photos this year since we wanted to highlight the video piece, although takedowns there have increased as well. And for business profiles, we wanted to share a different perspective by talking about the number of attempts to CLAIM business profiles that don't belong to them vs. attempts to CREATE fake business profiles; our enforcement number there has stayed steady."
Here is the chart I have been keeping tabs on from year to year:
Year | Reviews | Photos | Videos | Profiles |
2023 | 170 | N/A | 14 | 12 |
2022 | 115 | 200 | 7 | 20 |
2021 | 95 | 190 | 5 | 19 |
2020 | 55 | 160 | 3.5 | 3.6 |
2019 | 75 | 10 | 3 | 4 |
Here is a chart:
How did Google improve its algorithm for spam reviews? Google said they "launched a new machine learning algorithm that detects questionable review patterns even faster. It does so by examining longer-term signals on a daily basis — like if a reviewer leaves the same review on multiple businesses or if a business receives a sudden spike in 1 or 5-star reviews. In 2023, this new algorithm helped us take down 45% more fake reviews than the year before."
Google wrote:
This update works to catch both one-off cases and broader attack patterns. For example, a network of scammers falsely claimed that for a low fee they would connect people to high-paying online tasks, like writing fake reviews or clicking ads across the internet. Our new algorithm quickly identified this surge in suspicious reviews thanks to its ability to continuously analyze patterns, like whether an account had previously posted reviews.From there, our team of investigators analyzed reports from merchants who recently saw a spike in fake 5-star reviews, and even worked with people who were contacted by scammers on other platforms. Once we pinpointed patterns, like what categories of businesses were being targeted, we refined our algorithms to help protect hundreds of targeted businesses from the bad actors.
In just a few weeks, we caught over five million fake review attempts related to this scam. To prevent this scam from impacting others, we quickly disabled the malicious accounts associated with the scam and placed protections on hundreds of businesses. We also shared tips with our community about spotting scams so they could stay informed and vigilant. Thanks to our rapid detection and resolution, this scam ring no longer poses a threat to our review and rating system.
Meanwhile, local SEOs are like, nope, fake reviews are a big issue:
In case you're wondering how fake reviews are going on Google, I just sent this to Google because it's been denied now twice. Apparently it's not obvious enough that this is the same person reviewing a business multiple times 🤦♀️ pic.twitter.com/r7MZ0Yjf8V
— Joy Hawkins (@JoyanneHawkins) February 12, 2024
But not all:
They did get better at removing them.
— Len (@lenraleigh) February 13, 2024
It is weird that they won't remove them from LSA accounts.
What do you think? Take this poll:
Do you think Google’s fake reviews/profiles problem is now worse or better than 2 years ago? cc: @rustybrick @DataBoyd
— Greg Sterling 🇺🇦 (@gsterling) February 13, 2024
Forum discussion at X.