A detailed survey and comparative study of sentiment analysis algorithms

Harsha Sinha, A. Kaur
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引用次数: 10

Abstract

Sentiment Analysis is the process of figuring out the emotions from a piece of writing that whether it is positive, negative or neutral and is used to tell the speaker's attitude. The trend, today, is to consider the opinions of a variety of individuals around the globe before purchasing an item using micro-blogging data. Customers tend to go over a lot of reviews about a particular item before buying it. Sentiment Analysis makes this task easy for the customers. Sentiment Analysis aims to achieve its function in the simplest manner with the help of an existing approach and an existing algorithm. This paper focuses on the various Sentiment Analysis algorithms available in the existing literature. Further, this paper presents the comparative study of different Sentiment Analysis algorithms on the basis of accuracy.
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对情感分析算法进行了详细的调查和比较研究
情感分析是从一篇文章中找出情绪是积极的,消极的还是中性的过程,用来告诉说话者的态度。如今的趋势是,在使用微博数据购买商品之前,考虑全球各种个人的意见。顾客在购买某件商品之前往往会浏览很多关于它的评论。情感分析使这项任务对客户来说很容易。情感分析的目的是借助现有的方法和算法,以最简单的方式实现其功能。本文重点介绍了现有文献中可用的各种情感分析算法。在此基础上,对不同情感分析算法的准确率进行了比较研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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