Opinion Word Expansion and Target Extraction through Double Propagation
Opinion Word Expansion and Target Extraction through Double Propagation
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DOI：
10.1162/coli_a_00034
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发表时间：
2011-03-01
影响因子：
9.3
通讯作者：
Chen, Chun
中科院分区：
文献类型：
--
作者：
Qiu, Guang;Liu, Bing;Chen, Chun
观点分析，又称观点挖掘或情感分析，由于其许多实际应用和具有挑战性的研究问题，近年来引起了人们的极大关注。在本文中，我们研究了两个重要的问题，即观点词典的扩展和观点目标的提取。意见目标(简称目标)是指已表达意见的实体及其属性。为了完成任务，我们发现有几种句法关系将观点词和目标词联系在一起。可以使用依存关系解析器来识别这些关系，然后利用这些关系来扩展初始意见词典并提取目标。该方法基于Bootstrapping方法。我们称之为双重传播，因为它在观点词和目标之间传播信息。该方法的一个关键优点是，它只需要一个初始意见词典来启动自举过程。因此，由于使用了意见词种子，该方法是半监督的。在评估中，我们使用标准的产品评论测试集将所提出的方法与几种最先进的方法进行了比较。结果表明，该方法的性能明显优于已有的方法。
Analysis of opinions, known as opinion mining or sentiment analysis, has attracted a great deal of attention recently due to many practical applications and challenging research problems. In this article, we study two important problems, namely, opinion lexicon expansion and opinion target extraction. Opinion targets (targets, for short) are entities and their attributes on which opinions have been expressed. To perform the tasks, we found that there are several syntactic relations that link opinion words and targets. These relations can be identified using a dependency parser and then utilized to expand the initial opinion lexicon and to extract targets. This proposed method is based on bootstrapping. We call it double propagation as it propagates information between opinion words and targets. A key advantage of the proposed method is that it only needs an initial opinion lexicon to start the bootstrapping process. Thus, the method is semi-supervised due to the use of opinion word seeds. In evaluation, we compare the proposed method with several state-of-the-art methods using a standard product review test collection. The results show that our approach outperforms these existing methods significantly.