Dual Sentiment Analysis: Considering Two Sides of One Review | |
Xia, Rui1; Xu, Feng2; Zong, Chengqing3![]() | |
刊名 | IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
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2015-08-01 | |
卷号 | 27期号:8页码:2120-2133 |
关键词 | Natural language processing machine learning sentiment analysis opinion mining |
英文摘要 | Bag-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. |
WOS标题词 | Science & Technology ; Technology |
类目[WOS] | Computer Science, Artificial Intelligence ; Computer Science, Information Systems ; Engineering, Electrical & Electronic |
研究领域[WOS] | Computer Science ; Engineering |
关键词[WOS] | CLASSIFICATION |
收录类别 | SCI |
语种 | 英语 |
WOS记录号 | WOS:000357692600009 |
公开日期 | 2015-12-24 |
内容类型 | 期刊论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/8867] ![]() |
专题 | 自动化研究所_模式识别国家重点实验室_自然语言处理团队 |
作者单位 | 1.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 |
推荐引用方式 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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