Synchronous social question-and-answer (Q&A) systems match askers to answerers and support real-time dialog between them to resolve questions. These systems typically find answerers based on the degree of expertise match with the asker\u2019s initial question. However, since synchronous social Q&A involves a dialog between asker and answerer, differences in expertise may also matter (e.g., extreme novices and experts may have difficulty establishing common ground). In this poster we use data from a live social Q&A system to explore the impact of expertise differences on answer quality and aspects of the dialog itself. The findings of our study suggest that synchronous social Q&A systems should consider the relative expertise of candidate answerers with respect to the asker, and offer interactive dialog support to help establish common ground between askers and answerers.<\/p>\n","protected":false},"excerpt":{"rendered":"
Synchronous social question-and-answer (Q&A) systems match askers to answerers and support real-time dialog between them to resolve questions. These systems typically find answerers based on the degree of expertise match with the asker\u2019s initial question. 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