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'I Know What You Feel': Analyzing the Role of Conjunctions in Automatic Sentiment Analysis

机译:“我知道您的感受”:分析连词在自动情感分析中的作用

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We are interested in finding how people feel about certain topics. This could be considered as a task of classifying the sentiment: sentiment could be positive, negative or neutral. In this paper, we examine the problem of automatic sentiment analysis at sentence level. We observe that sentence structure has a fair contribution towards sentiment determination, and conjunctions play a major role in defining the sentence structure. Our assumption is that in presence of conjunctions, not all phrases have equal contribution towards overall sentiment. We compile a set of conjunction rules to determine relevant phrases for sentiment analysis. Our approach is a representation of the idea to use linguistic resources at phrase level for the analysis at sentence level. We incorporate our approach with support vector machines to conclude that linguistic analysis plays a significant role in sentiment determination. Finally, we verify our results on movie, car and book reviews.
机译:我们有兴趣寻找人们对某些主题的感觉。这可以被认为是对情绪进行分类的任务:情绪可以是积极的,消极的或中立的。在本文中,我们研究了句子层面的自动情感分析问题。我们观察到句子结构对情绪确定具有公平的贡献,并且连词在定义句子结构中起着重要作用。我们的假设是,在存在连词的情况下,并非所有短语对整体情感都有相同的贡献。我们编译了一组连接规则,以确定用于情感分析的相关短语。我们的方法代表了使用短语级别的语言资源进行句子级别分析的想法。我们将我们的方法与支持向量机结合在一起,得出结论,语言分析在情感确定中起着重要作用。最后,我们在电影,汽车和书评中验证我们的结果。

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