Social and collaborative information seeking: panel

In recent years, information retrieval and information seeking have moved beyond their single-user roots and are becoming multi-user endeavors. However, there are multiple visions for how best to design multi-user interactions: social search versus collaborative search. The terms "social" and "collaborative" are overloaded with meaning, having been used to describe a wide variety of systems, user needs and goals, interaction styles, and algorithms. In this panel we adopt the following primary definitions: Information seeking tasks in which there are two or more people who lack the same information (share the same information need) and explicitly set out together to satisfy that need are known as collaborative. A collaborative information retrieval system provides mechanisms -- interfaces and mediation algorithms -- that allow the team to work together to find information that neither individual would have found when working alone. There is an inherent division of labor in collaborative work. On the other hand, information seeking tasks in which only a single individual lacks information, but is willing or able to let an larger group assist in the satisfaction of that need, is known as social search. The larger group may be an community of like-minded individuals, or it might be a social network of friends and associates. But either way, the assumption is that someone in that community or network already possesses the information that the initial individual seeks. The goal of the system is therefore to correctly propagate or diffuse that existing knowledge throughout the network, to amplify and repeat information that has already been discovered by at least one person. Despite these fundamental differences between collaborative (team-oriented, jointly-held information need) and social (network- and community-augmented, though ultimately solitary need), there are similarities in process. This panel will explore both these similarities and differences, and provide insight about whether one type of multi-user information seeking vision will ultimately eclipse the other, or whether each will remain separate but complementary.