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Social search or a social search engine is a type of web search method that determines the relevance of search results by considering the interactions or contributions of users

Benefits To date social search engines have not demonstrated measurably improved search results over algorithmic search engines. However, there are potential benefits deriving from the human input qualities of social search. Reduced impact of link spam by relying less on link structure of web pages. Increased relevance because each result has been selected by users. Leverage a network of trusted individuals by providing an indication of whether they thought a particular result was good or bad. The introduction of 'human judgement' suggests that each web page has been viewed and endorsed by one or more people, and they have concluded it is relevant and worthy of being shared with others using human techniques that go beyond the computer's current ability to analyze a web page. Web pages are considered to be relevant from the reader's perspective, rather than the author who desires their content to be viewed, or the web master as they create links. More current results. Because a social search engine is constantly getting feedback it is potentially able to display results that are more current or in context with changing information.

Concerns Risk of spam. Because users can directly add results to a social search engine there is a risk that some users could insert search spam directly into the search engine. Elimination or prevention of this spam would require the ability to detect the validity of a user's' contribution, such as whether it agrees with other trusted users. "The Long Tail" of search is a concept that there are so many unique searches conducted that most searches, while valid, are performed very infrequently. A search engine that relied on users filling in all the searches would be at a disadvantage to one that used machines to crawl and index the entire web.

he concept of social ranking can be considered to derive from Google's PageRank algorithm,[citation needed] which assigns importance to web pages based on analysis of the link structure of the web, because PageRank is relying on the collective judgment of webmasters linking to other content on the web. Links, in essence, are positive votes by the webmaster community for their favorite sites.

Brands are especially worried about negative comments hurting a brand, but they also know that they need to go social. That's why they're using Facebook and Twitter with some success

Of all social media, Facebook drew the most interest of respondents, followed by Twitter. Tying for third place were customer reviews and blogs. Viral videos took fifth.

consumers listen to their peers