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Sentiment analysis of movie reviews: A new feature-based heuristic for aspect-level sentiment classification

机译:电影评论的情感分析:基于新特征的启发式方面层面的情感分类

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This paper presents our experimental work on a new kind of domain specific feature-based heuristic for aspect-level sentiment analysis of movie reviews. We have devised an aspect oriented scheme that analyses the textual reviews of a movie and assign it a sentiment label on each aspect. The scores on each aspect from multiple reviews are then aggregated and a net sentiment profile of the movie is generated on all parameters. We have used a SentiWordNet based scheme with two different linguistic feature selections comprising of adjectives, adverbs and verbs and n-gram feature extraction. We have also used our SentiWordNet scheme to compute the document-level sentiment for each movie reviewed and compared the results with results obtained using Alchemy API. The sentiment profile of a movie is also compared with the document-level sentiment result. The results obtained show that our scheme produces a more accurate and focused sentiment profile than the simple document-level sentiment analysis.
机译:本文介绍了我们针对一种新型的基于领域特定特征的启发式方法进行的实验工作,该方法用于电影评论的方面级情感分析。我们设计了一种面向方面的方案,该方案可以分析电影的文字评论,并在每个方面为其分配一个情感标签。然后汇总来自多个评论的每个方面的分数,并在所有参数上生成电影的净情感特征。我们使用了基于SentiWordNet的方案,该方案具有两个不同的语言特征选择,包括形容词,副词和动词以及n-gram特征提取。我们还使用了SentiWordNet方案来计算每部电影的文档级情感,并将结果与​​使用Alchemy API获得的结果进行比较。电影的情感配置文件也将与文档级别的情感结果进行比较。获得的结果表明,与简单的文档级情感分析相比,我们的方案产生了更准确,更集中的情感简介。

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