Your best might not be good enough: Ranking in collaborative social search engines

A relevant feature of online social networks like Facebook is the scope for users to share external information from the web with their friends by sharing an URL. The phenomenon of sharing has bridged the web graph with the social network graph and the shared knowledge in ego networks has become a source for relevant information for an individual user, leading to the emergence of social search as a powerful tool for information retrieval. Consideration of the social context has become an essential factor in the process of ranking results in response to queries in social search engines. In this work, we present InfoSearch, a social search engine built over the Facebook platform, which lets users search for information based on what their friends have shared. We identify and implement three distinct ranking factors based on the number of mutual friends, social group membership, and time stamp of shared documents to rank results for user searches. We perform user studies based on the Facebook feeds of two authors to understand the impact of each ranking factor on the result for two queries.