RealQA: Real-Time Community Question Answering

This page provides the source code and data for the following paper:

Qiaoling Liu, Tomasz Jurczyk, Jinho D. Choi, and Eugene Agichtein. Real-Time Community Question Answering: ExploringContent Recommendation and User Notification Strategies. In Proceedings of the 2015 International Conference on Intelligent User Interfaces, IUI ’15, ACM (New York, NY, USA, 2015).

Community-based Question Answering (CQA) services allow users to find and share information by interacting with others. A key to the success of CQA services is the quality and timeliness of the responses that users get. With the increasing use of mobile devices, searchers increasingly expect to find more local and time-sensitive information, such as the current special at a cafe around the corner. Yet, few services provide such hyper-local and time-aware question answering. This requires intelligent content recommendation and careful use of notifications (e.g., recommending questions to only selected users). To explore these issues, we developed {\em RealQA}, a real-time CQA system with a mobile interface, and performed two user studies: a formative pilot study with the initial system design, and a more extensive study with the revised UI and algorithms. The research design combined qualitative survey analysis and quantitative behavior analysis under different conditions. We report our findings of the prevalent information needs and types of responses users provided, and of the effectiveness of the recommendation and notification strategies on user experience and satisfaction. Our system and findings offer insights and implications for designing real-time CQA systems, and provide a valuable platform for future research.