Social Search began as a Google Labs experiment that aimed to bring search results to people that was morepersonalized. Social search engine is an enhanced version of a search engine that combines traditional algorithm driven technology with online community filtering to produce highly personalized results. A few social search engines depend only on online communities. Depending on the feature-set of a particular search engine, these results may then be saved and added to community search results, further improving the relevance of results for future searches of that keyword.
Social search engines are considered a part of Web 2.0 because they use the collective filtering of online communities to elevate particularly interesting or relevant content using tagging. These descriptive tags add to the Meta data embedded in Web pages, theoretically improving the results for particular keywords over time. A user will generally see suggested tags for a particular search term, indicating tags that have previously been added.

Your friends and contacts are a key part of your life online. Most people on the web today make social connections and publish web content in many different ways, including blogs, status updates and tweets. This translates to a public social web of content that has special relevance to each person. Unfortunately, that information isn't always very easy to find in one simple place. That's why today Google is rolling out a new experiment on Google Labs called Google Social Search that helps you find more relevant public content from your broader social circle. It should be available for everyone to try by the end of the day
The spiders of Search plus Your World — as Social Search is now known — particularly favor the social network Google+, meaning that anything you or your friends have posted on Google+ will influence your search results and is more likely to appear in searches.
Potential drawbacks to social search lie in its open structure, as is the case with other tagged databases. As these are trust-based networks, unintentional or malicious misuse of tags in this context can lead to imprecise search results.

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