Purpose: The purpose of this paper is to introduce the notion of social search as a new concept, drawing upon the patterns of web search behaviour. It aims to: define social search; present a taxonomy of social search; and propose a user-centred social search method. Design/methodology/approach: A mixed method approach was adopted to investigate and conceptualise the notion of social search. A review of literature on social search was carried out to identify the key trends and topics. A model of online collaboration was adopted to delineate the types and categories of social search. Four use case scenarios were developed to provide a more pragmatic approach to the understanding of social search. Findings: The developed taxonomy of social search reveals important similarities and differences between many social search systems. This analysis reveals a gap in social search approaches. A practical method was identified that allows users to directly leverage social search without special features built into search engines. Research limitations/implications: For feasibility reasons, Google was used as an example of a search system that can be used for carrying out social searches. Practical implications: The paper provides several practical implications for web searchers as well as web designers. In particular, some recommendations are provided for the design of search engines, digital libraries and browser add-ons. Social implications: The study demonstrates the value and power of "collective intelligence" in web search. It shows how general web searches can be enhanced through using socially enhanced web-based tools such as social bookmarking systems, social tagging services and social media sites. Originality/value: This is the first study that provides a granular analysis of the notion of social search and puts forward a taxonomy of social search. The use cases developed and reported are created based on real search topics, and show the value and validity of the approach taken. (Contains 1 table and 6 figures.)