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Sentiment analysis of movie reviews based on dictionary and weak tagging information
FAN Zhen, GUO Yi, ZHANG Zhenhao, HAN Meiqi
Journal of Computer Applications    2018, 38 (11): 3084-3088.   DOI: 10.11772/j.issn.1001-9081.2018041245
Abstract742)      PDF (804KB)(694)       Save
Focused on the time-consuming and laborious problem of data annotation in review text sentiment analysis, a new automatic data annotation method was proposed. Firstly, the sentiment tendency of the review text was calculated based on the sentiment dictionary. Secondly, the review text was automatically annotated by using the weak tagging information of the user and the sentiment tendency based on the dictionary. Finally, Support Vector Machine (SVM) was used to classify the sentiment of the review text. The proposed method reached 77.2% and 77.8% respectively in the accuracy of sentiment classification on two types of data sets, which were 1.7 percentage points and 2.1 percentage points respectively higher than those of the method only based on user rating. The experimental results show that the proposed method can improve the classification effect in movie reviews sentiment analysis.
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