A Novel Approach for Sentiment Classification by Using Convolutional Neural Network

被引:0
作者
Kalaivani, M. S. [1 ]
Jayalakshmi, S. [2 ]
机构
[1] Tagore Coll Arts & Sci, Chennai, Tamil Nadu, India
[2] Vels Inst Sci Technol & Adv Studies, Chennai, Tamil Nadu, India
来源
PROCEEDINGS OF SECOND INTERNATIONAL CONFERENCE ON SUSTAINABLE EXPERT SYSTEMS (ICSES 2021) | 2022年 / 351卷
关键词
Sentiment analysis; Deep learning; Word embedding; Convolutional neural network; Max pooling layer; Fully connected layer;
D O I
10.1007/978-981-16-7657-4_13
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Social media platforms facilitate communication and data exchange. There is a substantial number of opinionated information available in digital form. It is essential to validate unstructured Web data in order to extract knowledge from it. Sentiment analysis offers a wide variety of applications across all domains. The primary objective of sentiment analysis is to asses if the input text is positive or negative. When a buyer purchases a product, they submit feedback of the product. These reviews are essential for getting a general sense of how people feel about the product or service. Customer reviews on the Internet help to make purchases. Sentiment analysis results assist businesses, understand customer expectations, and enhance service and product quality. Several deep learning algorithms have been used in this sector with promising results. This paper suggests a deep learning approach for sentiment analysis by using convolutional neural networks.
引用
收藏
页码:143 / 152
页数:10
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