An experimental study of common ground in text-based communication
CHI '91 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Information sought and information provided: an empirical study of user/expert dialogues
CHI '85 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
A probabilistic model of information retrieval: development and comparative experiments
Information Processing and Management: an International Journal
Formal models for expert finding in enterprise corpora
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
The anatomy of a large-scale social search engine
Proceedings of the 19th international conference on World wide web
Effects of community size and contact rate in synchronous social q&a
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
A user-oriented model for expert finding
ECIR'11 Proceedings of the 33rd European conference on Advances in information retrieval
| Hi-index | 0.00 |
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's 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.