Investigating Users’ Needs and Behavior for Social Search

Traditional Web search systems have limitations due to its unrealistic assumption on users’ query formulation and lack of context-sensitivity. To overcome these limitations, we designed and implemented a social search system which is based on a social adaptive navigation system Knowledge Sea and exploits the past usage history of users. By conducting a survey and transaction log analysis, we could observe users’ strong attitudes to the need for the social search capability. We could also observe their active use of the new feature and change of behavior while they were using the search system. At the initial stage of our experiment, users did not show big difference in their usage of the system compared to the conventional search services but as time passes and the usage history accumulates, meaningful changes in their behavior toward the use of social navigation support features of the system were discovered.