About a month ago, Google unveiled the “Panda” algorithm change that targeted low quality content sites. Around the same time, they released a feature for the Google Chrome browser that gave users an option to block a site from showing up in their personal search results.
Thus — if you’re using Google Chrome as your browser — if you search for something and get what you think is a crummy content farm, you can click a button and never see that site show up in your results again.
And of course, Google gets to gather all that information on how many times each site has been blocked.
Google was clear that they did not use that as a ranking signal in the Panda algorithm change; however, they did compare the effects of the Panda change to that block list, and found an 84% overlap, which they considered an excellent signal that they were on the right path.
Google incorporates user blocked sites into the Panda algorithm
Yesterday Google announced an update to their algorithm that will take all of that data on blocked sites and use it as a ranking signal. So now when tons of people choose to delete a site from their search results, that information may be used to downrank that site from everyone’s search results.
In some high-confidence situations, we are beginning to incorporate data about the sites that users block into our algorithms. In addition, this change also goes deeper into the “long tail” of low-quality websites to return higher-quality results where the algorithm might not have been able to make an assessment before.
Google also stated that this change will be much smaller in scope than the original Panda algorithm update, affecting only about 2% of search queries, rather than the 12% that Panda affected.
We’ll have to wait and see whether this is a change that can be effectively gamed (say, by encouraging a mass of Twitter followers to do a search with Chrome and block the competition) but if this algorithm update is finally going to get crummy eHow and Yahoo Ask garbage out of my search results, I welcome it!
Other Panda-Related Posts:
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