Social search is the category of web search that makes use of the social graph of the user who is conducting the search. Social search utilizes many things including shared bookmarks, content tagging, and even sophisticated computer algorithms to derive results. The principle behind social search is that instead of computer algorithms deciding the results for specific queries, human network oriented results would be more meaningful and relevant for the user.
The social groups associated with a user could be used in the search engine, so that the data that are returned would be enhanced to suit the user’s needs.
The benefits of social search are:
- Since the social groups stem from content streams of users, the results would be more relevant to the user and the needs.
- It can help in building a human network which can be trusted.
- Since the results are products of human involvement, it can be more helpful and relevant and would also help in bettering computer algorithms to suit different human networks.
- Negligible spamming occurs through social search, as it is more based on personal feedback.
- Social search also provides results which are current and up to date as there is a constant feedback loop involved.
- More business and traffic can be derived based on social graphs.
Negatives of social search:
- Without proper control, users can corrupt the search results with spam results.
- The long search terms e,ployed by users are not suited for social search as they are rarely used.