一种改进的舆情分析技术——ⅱ

Chintan Panjwani, Rashmi K. Thakur
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引用次数: 0

摘要

增强型双情感分析(EDSA)是一种改进的系统,它提高了现有的双情感分析(DSA)的性能。它主要侧重于通过对现有的DSA方法进行一些修改来提高现有系统的效率。EDSA提高了公众评论的分类准确性。除了分类精度外,EDSA还考虑了精度、召回率和度量。在第一阶段,对数据进行预处理,对数据进行清理,其中进行主观性分析,获得主观评价,仅对主观评价进行情感分析。第二阶段进行否定检测和情感词反转,获得反转评论。第三阶段对原始评论和反向评论进行极性计算,根据评论的情感得分获得正面和负面评论。第四阶段执行增强的双重训练和预测,其中将正面和负面评论提供给各种分类器,这些分类器将最终结果作为输出。最后一个阶段是从前一阶段获得的各种参数值的图形表示,这有助于比较各种分类器的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Enhanced Technique for Analyzing Sentiments of Public Reviews - II
Enhnaced Dual Sentiment Analysis (EDSA) is an improved system which enhances the performance of the existing Dual Sentiment Analysis (DSA) which is implemented in literature. It mainly focuses on improving the efficiency of the existing system by making some modifications to the existing DSA approach. EDSA improves the classification accuracy of the public reviews. Apart from the classification accuracy other parameters considered in EDSA are precision, recall and fmeasure. In the first phase, a data pre-processing is performed to clean the data where subjectivity analysis is performed to obtain the subjective reviews and sentiment analysis is performed on subjective reviews only. Second phase deals with negation detection and sentiment word sreversal to obtain the reversed reviews. Third phase performs polarity calculation on the original and reversed reviews to obtain positive and negative reviews based on sentiment score of the reviews. Fourth phase performs the enhanced dual training and prediction where the positive and negative reviews are provided to various classifiers which provides the final results as the output. Final phase is the graphical representation of the various parameter values obtained from the previous phase which helps in comparing the results of the various classifiers.
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