情感分类任务旨在识别文本所表达的情感色彩信息(例如,褒或者贬,支持或者反对)。该文提出一种基于情绪词的中文情感分类方法,使用大规模未标记数据和少量情绪词实现情感分类。具体来讲,首先使用情绪词从未标注数据中抽取高正确率的自动标注数据作为训练样本,然后采用半监督学习方法训练分类器进行情感分类。实验表明,该文提出的方法在产品评论与酒店评论两个领域的情感分类任务中取得了较好地分类效果。
Abstract
Sentiment classification is to distinguish the text between the expressed sentiment categories, such as positive vs. negative or agree vs. disagree. This paper aims to perform unsupervised sentiment classification with only unlabeled data and a small scale of emotion words. In detail, we firstly adopted the emotion words to extract the automatically-labeled samples with high precision, and then used these samples with the unlabeled samples to perform semi-supervised learning for sentiment classification. Experimental results demonstrate that this approach can achieve a good performance for the task of sentiment classification in both product and hotel domains.
Key wordssentiment classification; emotion words; unsupervised learning; co-training
关键词
情感分类 /
情绪词 /
非监督学习 /
协同训练
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Key words
sentiment classification /
emotion words /
unsupervised learning /
co-training
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参考文献
[1] 姚天昉,程希文,徐飞玉,等. 文本意见挖掘综述[J]. 中文信息学报,2008,22(3): 71-80.
[2] Pang B.,L. Lee. Opinion Mining and Sentiment Analysis[J]. Foundations and Trends in Information Retrieval, 2008, 2(1-2): 1-135.
[3] 周立柱,贺宇凯,王建勇. 情感分析研究综述[J]. 计算机应用,2008,28(11): 2725-2728.
[4] Li S., Huang C., Zhou G., et al.. Employing Personal/Impersonal Views in Supervised and Semi-supervised Sentiment Classification[C]//Proceedings of Annual Meeting on Association for Computational Linguistics (ACL-10). 2010: 414-423.
[5] Dasgupta S., V. Ng. Mine the Easy and Classify the Hard: Experiments with Automatic Sentiment Classification[C]//Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP (ACL-IJCNLP-09). 2009.
[6] Turney P. Thumbs up or thumbs down? Semantic Orientation Applied to Unsupervised Classification of Reviews[C]//Proceedings of Annual Meeting on Association for Computational Linguistics (ACL-02), 2002.
[7] Blitzer J., Dredze M., F. Pereira. Biographies, Bollywood, Boom-boxes and Blenders: Domain Adaptation for Sentiment Classification[C]//Proceedings of Annual Meeting on Association for Computational Linguistics (ACL-07). 2007: 440-447.
[8] Kennedy A., D. Inkpen. Sentiment Classification of Movie Reviews using Contextual Valence Shifters[C]//Proceedings of Computational Intelligence. Publisher: John Wiley & Sons, 2006: 110-125.
[9] 朱嫣岚,闵锦,周雅倩,等. 基于HowNet的词汇语义倾向计算[J]. 中文信息学报,2006,20(1): 14-20.
[10] Zagibalov T., J. Carroll. Automatic Seed Word Selection for Unsupervised Sentiment Classification of Chinese Test[C]//Proceedings of the 22rd International Conference on Computational Linguistics (COLING-08). 2008.
[11] Lin C., He Y., R. Everson. A Comparative Study of Bayesian Models for Unsupervised Sentiment Detection[C]//Proceeding of Annual Meeting on Association for Computational Linguistics(ACL-10). 2010: 144-152.
[12] 许小颖,陶建华. 汉语情感系统中情感划分的研究[C]//第一届中国情感计算及智能交互学术会议. 2003.
[13] Clark S., Curran J., M. Osborne. Bootstrapping POS Taggers Using Unlabelled Data[C]//Proceedings of the 7th Conference on Natural Language Learning at the Human Language Technologies and North American Association for Computational Linguistics (HLT-NAACL). 2003: 49-55.
[14] Blum A., Mitchell T. Combining Labeled and Unlabeled Data with Co-training[C]//Proceedings of the Workshop on Computational Learning Theory. 1998: 92-100.
[15] Pang B., Lee L., S. Vaithyanathan. Thumbs up? Sentiment Classification using Machine Learning techniques[C]//Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP-02). 2002.
[16] Cui H., Mittal V., M. Datar. Comparative Experiments on Sentiment Classification for Online Product Reviews[C]//Proceedings of the 21st National Conference on Artificial Intelligence. Menlo Park: AAAI Press. 2006: 1265-1270.
[17] 唐慧丰,谭松波,程学旗. 基于监督学习的中文情感分类技术比较研究[J]. 中文信息学报,2007,21(6): 88-94.
[18] Wan X. Co-Training for Cross-Lingual Sentiment Classification[C]//Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP (ACL-IJCNLP-09). 2009.
[19] Bollegala D., Weir D., J. Carroll. Using multiple sources to construct a sentiment sensitive thesaurus for cross-domain sentiment classification[C]//Proceedings of Annual Meeting on Association for Computational Linguistics (ACL-11). 2011: 132-141.
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脚注
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基金
国家自然科学基金(60970056,61070123,61003155);高等学校博士学科点专项科研基金(20093201110006);模式识别国家重点实验室开放课题基金
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