Question Identification on Twitter, Accepted by CIKM 2011
Venue
Proceedings of the 20th ACM international conference on Information and knowledge management, ACM, New York, NY, USA (2011)
Publication Year
2011
Authors
Baichuan Li, Xiance Si, Michael R. Lyu, Irwin King, Edward Y. Chang
BibTeX
Abstract
In this paper, we investigate the novel problem of auto- matic question
identification in the microblog environment. It contains two steps: detecting
tweets that contain ques- tions (we call them “interrogative tweets”) and
extracting the tweets which really seek information or ask for help (so called
“qweets”) from interrogative tweets. To detect inter- rogative tweets, both
traditional rule-based approach and state-of-the-art learning-based method are
employed. To extract qweets, context features like short urls and Tweet- specific
features like Retweets are elaborately selected for classification. We conduct an
empirical study with sampled one hour’s English tweets and report our experimental
re- sults for question identification on Twitter.
