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Google's Marissa Mayer Looks Beyond Universal Search to Social Search

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In an interview with VentureBeat, Google VP Marissa Mayer says that social search is one avenue Google is pursuing to improve relevance in future iterations of its search engine. The algorithms could incorporate search history from a searcher's Gmail contacts, or input from human experts, as startups like Mahalo, Search Wikia, Collarity and Eurekster are doing (in different ways).

Some ways to incorporate social data into search results that Mayer mentioned include:


  1. Labeling or annotating search results, similar to the way social bookmarking sites like del.icio.us and StumbleUpon let users add comments and tags to sites they find.

  2. Show results from "users like you," the technique used expertly by Amazon.com to help shoppers discover new products they may not have even known they wanted.

  3. Using aggregate search histories of friends (or Gmail contacts) to influence search results

When asked what Google will look like ten years from now, Mayer replied, "I think one way it will be better is in understanding more about you and understanding more about your social context: Who your friends are, what you like to do, where you are. It's hard to imagine that the search engine ten years from now isn't advised by those things."

Social search is expected by many to define the next generation of search. According to search historian Danny Sullivan, search 1.0 used on-page elements to rank pages, search 2.0 added external linking, and search 3.0 is the current state, with universal search and blended search. Search 4.0 will incorporate these social factors.


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