13 Facts About Social search

The idea behind social search is that instead of ranking search results purely based on semantic relevance between a query and the results, a social search system takes into account social relationships between the results and the searcher.

Social search takes many forms, ranging from simple shared bookmarks or tagging of content with descriptive labels to more sophisticated approaches that combine human intelligence with computer algorithms.

The principle behind social search is that human network oriented results would be more meaningful and relevant for the user, instead of computer algorithms deciding the results for specific queries.

In 2008, there were a few startup companies that focused on ranking search results according to one's social graph on social networks.

Companies in the social search space include Evam-SOCOTO Wajam, Slangwho, Sproose, Mahalo, Jumper 2.

Related searches

In January 2013, Facebook announced a new Social search engine called Graph Search still in the beta stages.

Facebook's Graph Social search utilized Facebook's user generated content to target users.

Social search discovery is the use of social preferences and personal information to predict what content will be desirable to the user.

One development that seeks to redefine search is the combination of distributed search with social search.

Since the data used by Social search engines belongs to the user they should have absolute control over it.

The infrastructure required for a Social search engine is already available in the form of thousands of idle desktops and extensive residential broadband access.

The solutions for secure social search are blind signature, zero knowledge proof and resource handler.

Besides above engineering explorations, a more fundamental and potential method is to develop social search systems based on the understanding of related neural mechanisms.