使用动态词汇进行Twitter情感分析

Hrithik Katiyar, Monika, Parveen Kumar, Ambalika Sharma
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引用次数: 6

摘要

技术总是导致研究工作的进步。今天,Twitter是数百万用户访问最多的社交网站之一。为人民表达意见的一个重要方式是通过互联网。观点往往反映了信念和感觉。为了了解意见的极性,可以进行情绪分析,这将让我们知道意见是消极的,中性的还是积极的。情感分析发现它在许多地方都有应用,比如客户对特定产品的意见是公司所知道的,电影评论意见或政治观点的情感分析。本文介绍了一种动态词汇技术,即词汇随着训练的进行而发展。实验结果表明,该方法的性能令人满意。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Twitter Sentiment Analysis using Dynamic Vocabulary
Technology has always led to advancements in research works. Today, Twitter is one of the most visited social networking sites by millions of users. A significant way of expressing the opinion for the people is through the Internet. Opinions tend to reflect beliefs as well as feelings. To know the polarity of the opinions a sentiment analysis can be done, this will let us know whether the opinion is negative, neutral or positive. Sentiment Analysis finds its applications in many places like an opinion of the customer on a particular product is to be known by the company, movie review opinion or sentiment analysis of political opinions. This paper introduced a technique of dynamic vocabulary, in which the vocabulary develops as the training is done. The experimental result shows the performance of the proposed technique is satisfactory.
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