Abstract Sentiment analysis of Chinese micro-blog text based on extended sentiment dictionary
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Sentiment analysis of Chinese micro-blog text based on extended sentiment dictionary

机译:基于扩展情感词典的中文微博文本情感分析

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AbstractMicro-blog texts contain complex and abundant sentiments which reflect user’s standpoints or opinions on a given topic. However, the existing classification method of sentiments cannot facilitate micro-blog topic monitoring. To solve this problem, this paper presents a sentiment analysis method for Chinese micro-blog text based on the sentiment dictionary to support network regulators’ work better. First, the sentiment dictionary can be extended by extraction and construction of degree adverb dictionary, network word dictionary, negative word dictionary and other related dictionaries. Second, the sentiment value of a micro-blog text can be obtained through the calculation of the weight. Finally, micro-blog texts on a topic can be classified as positive, negative and neutral. Experimental results show the effectiveness of the proposed method.HighlightsMicro-blog texts contain abundant sentiments which reflect users opinions.The existing sentimental classification method cannot help micro-blog topic monitoringThis paper presents a sentiment analysis method for Chinese micro -blog text.Three simplified sentiments are easily support micro-blog topic monitoring.
机译: 摘要 微博文字包含复杂而丰富的情感,反映了用户对特定主题的观点或看法。但是,现有的情感分类方法不能促进微博客话题的监测。为了解决这个问题,本文提出了一种基于情感词典的中文微博文本情感分析方法,以更好地支持网络监管者的工作。首先,情感词典可以通过程度副词词典,网络单词词典,否定单词词典和其他相关词典的提取和构建来扩展。其次,通过计算权重可以获得微博文本的情感价值。最后,关于某个主题的微博文本可以分为正面,负面和中性。实验结果表明了该方法的有效性。 突出显示 < ce:list id =“ d1e442”> Micro-博客文本包含反映用户意见的丰富情感。 现有的情感分类方法无法帮助监控微博主题 本文提出了一种中文微博客文本的情感分析方法。 三种简化的情绪很容易支持微博客主题监视。

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