Automatic Annotation of News Comments Emotion Based on PLSA
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    Abstract:

    In order to solve the problem of manually annotating large-scale corpus, this study, based on the model of Probabilistic Latent Semantic Analysis (PLSA), proposed a method of automatic emotional annotation for news comments. First of all, the "doc-topic" and "word-topic" probability matrixes were computed by PLSA model. Then, drawing upon the "word-topic" together with the ontology lexicon, the emotional categories of the topics were annotated, with the presupposition that the emotional category of words is similar to those of words within the topic which occurs most frequently. Finally, the automatic annotation was made via the "doc-topic", with the assumption that the emotional category of topics is equivalent to those of topics within the document which occurs most frequently. The experimental results showed that the accurate rate of the method proposed by this study reached about 90%.

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林江豪,顾也力,周咏梅,阳爱民.基于PLSA的新闻评论情绪类别自动标注方法.计算机系统应用,2019,28(1):207-211

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History
  • Received:May 21,2018
  • Revised:June 15,2018
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  • Online: December 27,2018
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