A novel method for recognizing emotions of weblog sentences
A novel method for recognizing emotions of weblog sentences
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DOI：
10.1109/sii.2013.6776631
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发表时间：
2013-12
期刊：
影响因子：
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通讯作者：
Lei Wang;F. Ren;Duoqian Miao
中科院分区：
文献类型：
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作者：
Lei Wang;F. Ren;Duoqian Miao
随着大量的在线资源不断增加（如博客，产品评论，新闻评论等），很难阅读它们并获得有用的信息，特别是情感信息。互联网在线信息的情感分析是近年来自然语言处理领域的研究热点。在现有的大多数研究中，单标签情感分析被许多科学家所研究，它往往忽略了人类情感的复杂性。基于中文情感语料Ren-CECps，构建了一个多标签情感主题模型，用于识别网络日志语句中的复杂情感。我们使用潜在的主题变量和情感变量来发现句子的复杂情感。实验结果表明，该模型对网络日志语句的混合情感识别是合理有效的。
With plenty of online resources constantly increasing (like weblog, product reviews, news reviews, etc.), it is difficult to read them and obtain the useful information, especially emotion information. The emotion analysis on internet online information has received much attention from natural language processing field in recent years. In most existing works, single-label emotion analysis have been studied by many scientists, it often ignores the complexity of human feelings. This paper is dedicated to construct the multi-label emotion topic model for recognizing the complicated emotions of weblog sentences based on Chinese emotion corpus Ren-CECps. We employ latent topic variables and emotion variables to find complex emotions of the sentence. The results of experiments indicate that the model is reasonable and effective in recognizing the mixed emotions of weblog sentences.