Paper Info
Title
Is this urgent?: exploring time-sensitive information needs in collaborative question answering
Abstract
As online Collaborative Question Answering (CQA) servicessuch as Yahoo! Answers and Baidu Knows are attracting users, questions, and answers at an explosive rate, the truly urgent and important questions are increasingly getting lost in the crowd. That is, questions that require immediate responses are pushed out of the way by the trivial but more recently arriving questions. Unlike other questions in collaborative question answering (CQA) for which users might be willing to wait until good answers appear, urgent questions are likely to be of interest to the asker only if answered in the next few minutes or hours. For such questions, late responses are either not useful or are simply not applicable. Unfortunately, current collaborative question-answering systems do not distinguish urgent questions from the rest, and could thus be ineffective for urgent information needs. We explore text- and data- mining methods for automatically identifying urgent questions in the CQA setting. Our results indicate that modeling the question context (i.e., the particular forum/category where the question was posted) can increase classification accuracy compared to the text of the question alone.
Year
DOI
Venue
2009
10.1145/1571941.1572091
SIGIR
Keywords
Field
DocType
urgent question,question context,classification accuracy,current collaborative,explosive rate,collaborative question answering,urgent information need,time-sensitive information need,baidu knows,cqa setting,important question,social media,data mining,information need,question answering system,question answering
Data mining,World Wide Web,Social media,Question answering,Information needs,Information retrieval,Computer science,Time sensitive,If and only if
Conference
Citations 
PageRank 
References 
8
0.55
5
Authors
4
Name
Order
Citations
PageRank
Yandong Liu159724.74
Nitya Narasimhan225822.49
Venu Vasudevan362159.19
Eugene Agichtein44549269.70