Direct Answers or Brief Informative Suggestions? Performance of Different Types of Search Assistance Tools on Different Types on Search Tasks

While search assistance tools can help users with their search in various ways, would they always be effective for every type of search task? This study explored the different performance between two kinds of search assistance tools on exploratory tasks and comparative tasks. A user study was conducted on an experimental web search interface with the search assistance widget displaying on the right-hand side. Each participant was asked to do exploratory and comparative tasks on each search assistance tool. We collected and analyzed data from participants’ web logs, pre-test and post-task questionnaires, and the semi-structured interviews by the end of the study sessions. The findings suggest the effectiveness of each type of search task is different between the two search assistance tools; the dimension assistance is more helpful in comparative tasks whereas the link-suggesting assistance is more favored by exploratory tasks.Master of Science in Information Scienc

Social Feedback: Social Learning from Interaction History to Support Information Seeking on the Web

Information seeking on the Web has become a central part of many daily activities. Even though information seeking is extremely common, there are many times when these tasks are unsuccessful, because the information found is less than ideal or the task could have been completed more efficiently. In unsuccessful information-seeking tasks, there are often other people who have knowledge or experience that could help improve task success. However, information seekers do not typically look for help from others, because tasks can often be completed alone (even if inefficiently). One of the problems is that web tools provide people with few opportunities to learn from one another’s experiences in ways that would allow them to improve their success. This dissertation presents the idea of social feedback. Social feedback is based on the theory of social learning, which describes how people learn from observing others. In social feedback, observational learning is enabled through the mechanism of interaction history – the traces of activity people create as they interact with the Web. Social feedback systems collect and display interaction history to allow information seekers to learn how to complete their tasks more successfully by observing how other people have behaved in similar situations. The dissertation outlines the design of two social-feedback systems, and describes two studies that demonstrate the real world applicability and feasibility of the idea. The first system supports global learning, by allowing people to learn new search skills and techniques that improve information seeking success in many different tasks. The second system supports local learning, in which people learn how to accomplish specific tasks more effectively and more efficiently. Two further studies are conducted to explore potential real-world challenges to the successful deployment of social feedback systems, such as the privacy concerns associated with the collection and sharing of interaction history. These studies show that social feedback systems can be deployed successfully for supporting real world information seeking tasks. Overall, this research shows that social feedback is a valuable new idea for the social use of information systems, an idea that allows people to learn from one another’s experiences and improve their success in many common real-world tasks