Google: Machine Learning Takes Care Of Most Obvious Spam
On the latest Search Off The Record podcast, John Mueller, Gary Illyes and Martin Splitt had a special guest from the Google Search Quality team named Duy Nguyen. He said that Google has built a "very effective and comprehensive machine-learning model that basically took care of most of the obvious spam."
He said that this machine learning model deals with most of the spam that let's his team spend more of their time to "focus on more important work." He added that the spam machine learning model "basically took over all the heavy lifting" to tackle this most obvious spam.
So for such low quality or spammy content, it's relatively easy. If you're a person and you look at a page that's full of gibberish, or in this case, guest books with spammy posts, you should be able to say that emphatically, "Yes, this is spam," within seconds. Even if it's more complicated, with a trained eye, it should take less than a minute to determine something is spammy or not. And as Google, we have all these signals and all this data that we've accumulated and analyzed and studied over the years. So, you know, it's entirely possible to collect those datas to study it and build things like machine-learning models to tackle spam.
Machine learning model is interesting because it has so many use cases. It recommends music for you, you trust it enough to drive cars around so you don't have to drive. So building machine-learning models for spams turns out to be a pretty natural step for us.
