Talk:Local search engine optimisation

Out of 16 sources over half (9) cite searchengineland.com is there some selection bias within the sources being chosen? Considering looking into these and finding more authoritative secondary and tertiary sources for some topics. - Kieran21 (talk) 03:38, 6 September 2019 (UTC)

A question more than a suggestion at this point. Does this actually need to be it's own article, or could it be merged into Search Engine Optimization? There are several areas within SEO that do not have their own articles (I've mentioned some of these on Talk over at SEO). - Kieran21 (talk) 03:37, 6 September 2019 (UTC)

{{Edit semi-protected|Local search engine optimisation|answered=yes}}

Within the "Fake reviews" section which highlights suggesting to Google for fake reviews, the bullet point "* Current Google algorithms do not identify unnatural review patterns. Abnormal review patterns often do not need human gauging and should be easily identified by algorithms. As a result, both fake listings and rogue reviewer profiles should be suspended." is outdated

A 2023 article from Google called [https://blog.google/products/maps/google-maps-fake-contributions-ai-machine-learning/ "New ways we tackle fake contributions on Google Maps"] identifies progress from 2022's updates, including "new machine learning models paired with our advanced automated and manual techniques helped us remove more fake content." It also addressed the blocking and removal of "over 115 million policy-violating reviews" and how Google "stopped 20 million attempts to create fake Business Profiles." This directly addresses the previous "Fake reviews" content regarding a lack of algorithmic identification of reviews and fake listing suspension.

A 2024 article from Google called [https://blog.google/products/maps/how-machine-learning-keeps-contributed-content-helpful/ "How machine learning keeps contributed content helpful"] identifies a new machine learning algorithm initially developed in 2023 to reduce fake reviews. It also specifically addresses the use of algorithms to assist in identifying and disabling malicious accounts and rogue reviewer profiles - "To prevent this scam from impacting others, we quickly disabled the malicious accounts associated with the scam and placed protections on hundreds of businesses."

Suggested wording with citations:

While Google did not publicize any algorithms in 2017 that specifically addressed capturing unnatural review patterns and fake listing or reviewer profile suspension, Google has since revealed machine learning and algorithm development to address those exact concerns starting in at least 2022. {{cite web |last1=Gupta |first1=Ashish |title=New ways we tackle fake contributions on Google Maps |url=https://blog.google/products/maps/google-maps-fake-contributions-ai-machine-learning/ |website=The Keyword |publisher=Google |access-date=11 September 2024 |date=2023-03-31}}{{cite web |last1=Pritchett |first1=Dan |title=How machine learning keeps contributed content helpful |url=https://blog.google/products/maps/how-machine-learning-keeps-contributed-content-helpful/ |website=The Keyword |publisher=Google |access-date=11 September 2024 |date=2024-02-13}} Chrisfootbridge (talk) 15:44, 11 September 2024 (UTC)

{{reflist-talk}}

:File:Red information icon with gradient background.svg Not done for now: The sources you've provided are from Google itself. Are there any independent third party sources that establish that these changes address the concerns? meamemg (talk) 17:50, 13 September 2024 (UTC)