Twitter Sentiment Analysis using Dynamic Vocabulary

被引:0
|
作者
Katiyar, Hrithik
Monika
Kumar, Parveen [1 ]
Sharma, Ambalika [1 ]
机构
[1] Indian Inst Technol Roorkee, Roorkee, Uttar Pradesh, India
关键词
Sentiment Analysis; Support Vector Machine; Index Construction;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
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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页数:4
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