The goal of this thesis is to expand the traditional information processing model into the social space by investigating the influence of domain expertise on the use of social information systems. A laboratory-based experiment was conducted to examine the information seeking, sharing, and learning processes of domain experts and novices using a traditional search engine and a social tagging system. Empirical data on information behavior, search strategies, information content and knowledge change were recorded and analyzed. Results showed that domain experts collected and shared more information than novices, providing support to the hypothesis that domain experts benefit more from social information systems. Results also showed that the social information system helped domain novices to find general information and facilitated knowledge learning on novices, but the system did not help them to find as much domain-specific knowledge as domain experts, providing support to the hypothesis that domain knowledge is critical for successful utilization of social cues provided by social information systems. Results from the current study also support the notion that there is a dynamic interaction between knowledge-in-the-head and knowledge-in-the-social-web while people are searching in a social information system. Although information seekers are more and more reliant on accessing information from the World Wide Web, the current results suggest that domain expertise is still important for information seekers to successfully find relevant information in both traditional and social information environments. Implications on the design of future social information systems that facilitate exploratory search are discussed.
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