CASIA OpenIR  > 模式识别国家重点实验室  > 自然语言处理
Dual Sentiment Analysis: Considering Two Sides of One Review
Xia, Rui1; Xu, Feng2; Zong, Chengqing3; Li, Qianmu1; Qi, Yong1; Li, Tao1,4
Source PublicationIEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
2015-08-01
Volume27Issue:8Pages:2120-2133
SubtypeReview
AbstractBag-of-words (BOW) is now the most popular way to model text in statistical machine learning approaches in sentiment analysis. However, the performance of BOW sometimes remains limited due to some fundamental deficiencies in handling the polarity shift problem. We propose a model called dual sentiment analysis (DSA), to address this problem for sentiment classification. We first propose a novel data expansion technique by creating a sentiment-reversed review for each training and test review. On this basis, we propose a dual training algorithm to make use of original and reversed training reviews in pairs for learning a sentiment classifier, and a dual prediction algorithm to classify the test reviews by considering two sides of one review. We also extend the DSA framework from polarity (positive-negative) classification to 3-class (positive-negative-neutral) classification, by taking the neutral reviews into consideration. Finally, we develop a corpus-based method to construct a pseudo-antonym dictionary, which removes DSA's dependency on an external antonym dictionary for review reversion. We conduct a wide range of experiments including two tasks, nine datasets, two antonym dictionaries, three classification algorithms, and two types of features. The results demonstrate the effectiveness of DSA in supervised sentiment classification.
KeywordNatural Language Processing Machine Learning Sentiment Analysis Opinion Mining
WOS HeadingsScience & Technology ; Technology
WOS KeywordCLASSIFICATION
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Information Systems ; Engineering, Electrical & Electronic
WOS IDWOS:000357692600009
Citation statistics
Cited Times:22[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/8867
Collection模式识别国家重点实验室_自然语言处理
Affiliation1.Nanjing Univ Sci & Technol, Sch Comp Sci & Engn, Nanjing 210046, Jiangsu, Peoples R China
2.Nanjing Univ Sci & Technol, Sch Econ & Management, Nanjing, Jiangsu, Peoples R China
3.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China
4.Florida Int Univ, Sch Comp & Informat Sci, Miami, FL 33199 USA
Recommended Citation
GB/T 7714
Xia, Rui,Xu, Feng,Zong, Chengqing,et al. Dual Sentiment Analysis: Considering Two Sides of One Review[J]. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING,2015,27(8):2120-2133.
APA Xia, Rui,Xu, Feng,Zong, Chengqing,Li, Qianmu,Qi, Yong,&Li, Tao.(2015).Dual Sentiment Analysis: Considering Two Sides of One Review.IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING,27(8),2120-2133.
MLA Xia, Rui,et al."Dual Sentiment Analysis: Considering Two Sides of One Review".IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 27.8(2015):2120-2133.
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