Paper: Question Difficulty Estimation in Community Question Answering Services

ACL ID D13-1009
Title Question Difficulty Estimation in Community Question Answering Services
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2013
Authors

In this paper, we address the problem of estimating question difficulty in community question answering services. We propose a competition-based model for estimating ques- tion difficulty by leveraging pairwise compar- isons between questions and users. Our ex- perimental results show that our model sig- nificantly outperforms a PageRank-based ap- proach. Most importantly, our analysis shows that the text of question descriptions reflects the question difficulty. This implies the pos- sibility of predicting question difficulty from the text of question descriptions.