Question Identification on Twitter, Accepted by CIKM 2011
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.
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.
Research Areas
