Co-presented by Will Evans (@semanticwill) and Brynn Evans (@brynn) at the Enterprise Search Summit West 2009.
Social search has the potential to improve search practices beyond what is possible with traditional informational retrieval algorithms. Two different models of social search should be incorporated into enterprise and conventional search systems today. Collective Search involves aggregating social metadata, trends, and previous tags, bookmarks, or information shared by social networks. Collaborative Search, or question-answering, occurs when two or more participants actively engage in an information seeking task. Interactions include everything from replying to a one-time question to dually negotiating the query formation and relevancy of specific results to arrive at a shared consensus of best fit. This talk will frame the relevant models of social search in the context of Brynn’s research, and discuss the potential benefits for both users as well as organizations. We will extend these trends and findings to concrete design considerations that we encourage system designers to consider in order to leverage social search capabilities within the enterprise.