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Text Analytics for Predicting Question Acceptance Rates
Fong, Simon1; Zhou, Suzy2; Moutinho, Luiz3
2015-07-01
Source PublicationIT Professional
ISSN1520-9202
Volume17Issue:4Pages:34-41
Abstract

Online community question answering (CQA) services have gained unprecedented popularity among users wanting to voluntarily exchange solutions without a fee. However, CQA faces two challenges: the growing volume of databases and the increasing number of questions left unanswered. This article proposes classification in text analytics as one way to predict how likely a posted question is to be answered. This involves evaluating the features that characterize the question to understand why community members are or aren't answering it. Insights from text analytics could help CQA managers guide users regarding posting etiquette, thereby retaining such services' appeal and ensuring healthy knowledge growth. This study presents a feasible solution to tackle these two problems in CQA, and does so with promising results - particularly in classification by data stream mining with accelerated swarm search feature selection. 

DOIhttps://doi.org/10.1109/MITP.2015.67
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Telecommunications
WOS SubjectComputer Science, Information Systems ; Computer Science, Software Engineering ; Telecommunications
WOS IDWOS:000361906500006
PublisherIEEE COMPUTER SOC, 10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1314 USA
The Source to ArticleEngineering Village
Fulltext Access
Citation statistics
Cited Times [WOS]:2   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Affiliation1.University of Macau, Macau SAR, China;
2.Mozat, Singapore;
3.University of Glasgow, United Kingdom
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Fong, Simon,Zhou, Suzy,Moutinho, Luiz. Text Analytics for Predicting Question Acceptance Rates[J]. IT Professional,2015,17(4):34-41.
APA Fong, Simon,Zhou, Suzy,&Moutinho, Luiz.(2015).Text Analytics for Predicting Question Acceptance Rates.IT Professional,17(4),34-41.
MLA Fong, Simon,et al."Text Analytics for Predicting Question Acceptance Rates".IT Professional 17.4(2015):34-41.
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