感伤词词典的构建

Eduard Constantin Dragut, Clement T. Yu, A. Sistla, W. Meng
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引用次数: 84

摘要

网络上有大量关于产品、服务、政府政策、机构等的评论、评论和报告。在这些评论中表达的意见影响人们如何看待这些实体。例如,一个产品有持续的好评很可能卖得好,而一个产品有大量的差评很可能卖得不好。我们的目标是建立一个比现有的情感词词典更大、更准确的情感词词典。我们引入了演绎规则,它将具有已知极性的单词作为输入,并产生具有极性的同义词集(一组具有定义的同义词)。具有推导出极性的同义词集可以用来进一步推导出其他单词的极性。实验结果表明,对于给定的包含D个词的情感词词典,可以推断出大约50%的D个词具有极性。我们进行了一项实验,以找出推导出的单词的随机样本的准确性。结果表明,其准确度与将一个人的判断与另一个人的判断进行比较大致相同。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Construction of a sentimental word dictionary
The Web has plenty of reviews, comments and reports about products, services, government policies, institutions, etc. The opinions expressed in these reviews influence how people regard these entities. For example, a product with consistently good reviews is likely to sell well, while a product with numerous bad reviews is likely to sell poorly. Our aim is to build a sentimental word dictionary, which is larger than existing sentimental word dictionaries and has high accuracy. We introduce rules for deduction, which take words with known polarities as input and produce synsets (a set of synonyms with a definition) with polarities. The synsets with deduced polarities can then be used to further deduce the polarities of other words. Experimental results show that for a given sentimental word dictionary with D words, approximately an additional 50% of D words with polarities can be deduced. An experiment is conducted to find the accuracy of a random sample of the deduced words. It is found that the accuracy is about the same as that of comparing the judgment of one human with that of another.
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