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A Structure for Opinion in Social Domains

机译:社会领域中的意见结构

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摘要

Opinion mining, as a sub-field of text mining, analyzes opinions expressed regarding an object, a topic, or an issue. An opinion is expressed by a person using some opinion terms or phrases regarding a target. Statistical studies show that the affective factors on opinions in product domains are different from those in social domains. Opinion verbs and ``I" have the most affective influences on opinions in social domains. This paper introduces a structure for opinions in social domains considering verb as its core. An outline for opinion extraction from text is also proposed. The defined structure is evaluated in the applications of sentence subjectivity classification and sentiment polarity classification at the sentence and document levels. Our experiments show that the performance of the proposed structure is slightly higher than the traditional machine learning techniques and some previous works.
机译:意见挖掘作为文本挖掘的子领域,可以分析有关对象,主题或问题的意见。一个人使用一些关于目标的观点术语或短语来表达观点。统计研究表明,产品领域意见的影响因素与社会领域不同。意见动词和“ I”对社会领域中的意见影响最大,本文介绍了以动词为核心的社会领域中的意见结构,并提出了从文本中提取意见的大纲,并对定义的结构进行了评估在句子和文档级别的句子主观性分类和情感极性分类的应用中,我们的实验表明,该结构的性能略高于传统的机器学习技术和一些先前的工作。

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