A study on sentiment analysis techniques of Twitter data

被引:0
作者
Alsaeedi A. [1 ]
Khan M.Z. [1 ]
机构
[1] Department of Computer Science, College of Computer Science and Engineering, Taibah University, Madinah
来源
International Journal of Advanced Computer Science and Applications | 2019年 / 10卷 / 02期
关键词
Bayesian algorithm; Ensembles; Hybrid; Sentiment; SVM; Text mining; Twitter; Web data;
D O I
10.14569/ijacsa.2019.0100248
中图分类号
学科分类号
摘要
The entire world is transforming quickly under the present innovations. The Internet has become a basic requirement for everybody with the Web being utilized in every field. With the rapid increase in social network applications, people are using these platforms to voice them their opinions with regard to daily issues. Gathering and analyzing peoples' reactions toward buying a product, public services, and so on are vital. Sentiment analysis (or opinion mining) is a common dialogue preparing task that aims to discover the sentiments behind opinions in texts on varying subjects. In recent years, researchers in the field of sentiment analysis have been concerned with analyzing opinions on different topics such as movies, commercial products, and daily societal issues. Twitter is an enormously popular microblog on which clients may voice their opinions. Opinion investigation of Twitter data is a field that has been given much attention over the last decade and involves dissecting "tweets" (comments) and the content of these expressions. As such, this paper explores the various sentiment analysis applied to Twitter data and their outcomes. © 2013 The Science and Information (SAI) Organization.
引用
收藏
页码:361 / 374
页数:13
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